import os AUTOGGUF_VERSION = "v1.7.3" class _Localization: def __init__(self): pass class _English(_Localization): def __init__(self): super().__init__() # General UI self.WINDOW_TITLE = "AutoGGUF (automated GGUF model quantizer)" self.RAM_USAGE = "RAM Usage:" self.CPU_USAGE = "CPU Usage:" self.BACKEND = "Llama.cpp Backend:" self.REFRESH_BACKENDS = "Refresh Backends" self.MODELS_PATH = "Models Path:" self.OUTPUT_PATH = "Output Path:" self.LOGS_PATH = "Logs Path:" self.BROWSE = "Browse" self.AVAILABLE_MODELS = "Available Models:" self.REFRESH_MODELS = "Refresh Models" # Model Import self.IMPORT_MODEL = "Import Model" self.SELECT_MODEL_TO_IMPORT = "Select Model to Import" self.CONFIRM_IMPORT = "Confirm Import" self.IMPORT_MODEL_CONFIRMATION = "Do you want to import the model {}?" self.MODEL_IMPORTED_SUCCESSFULLY = "Model {} imported successfully" self.IMPORTING_MODEL = "Importing model" self.IMPORTED_MODEL_TOOLTIP = "Imported model: {}" # GGUF Verification self.INVALID_GGUF_FILE = "Invalid GGUF file: {}" self.SHARDED_MODEL_NAME = "{} (Sharded)" self.IMPORTED_MODEL_TOOLTIP = "Imported model: {}" self.CONCATENATED_FILE_WARNING = "This is a concatenated file part. It will not work with llama-quantize; please concat the file first." self.CONCATENATED_FILES_FOUND = ( "Found {} concatenated file parts. Please concat the files first." ) # Plugins self.PLUGINS_DIR_NOT_EXIST = ( "Plugins directory '{}' does not exist. No plugins will be loaded." ) self.PLUGINS_DIR_NOT_DIRECTORY = ( "'{}' exists but is not a directory. No plugins will be loaded." ) self.PLUGIN_LOADED = "Loaded plugin: {} {}" self.PLUGIN_INCOMPATIBLE = "Plugin {} {} is not compatible with AutoGGUF version {}. Supported versions: {}" self.PLUGIN_LOAD_FAILED = "Failed to load plugin {}: {}" self.NO_PLUGINS_LOADED = "No plugins loaded." # GPU Monitoring self.GPU_USAGE = "GPU Usage:" self.GPU_USAGE_FORMAT = "GPU: {:.1f}% | VRAM: {:.1f}% ({} MB / {} MB)" self.GPU_DETAILS = "GPU Details" self.GPU_USAGE_OVER_TIME = "GPU Usage Over Time" self.VRAM_USAGE_OVER_TIME = "VRAM Usage Over Time" self.PERCENTAGE = "Percentage" self.TIME = "Time (s)" self.NO_GPU_DETECTED = "No GPU detected" self.SELECT_GPU = "Select GPU" self.AMD_GPU_NOT_SUPPORTED = "AMD GPU detected, but not supported" # Quantization self.QUANTIZATION_TYPE = "Quantization Type:" self.ALLOW_REQUANTIZE = "Allow Requantize" self.LEAVE_OUTPUT_TENSOR = "Leave Output Tensor" self.PURE = "Pure" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "Include Weights:" self.EXCLUDE_WEIGHTS = "Exclude Weights:" self.USE_OUTPUT_TENSOR_TYPE = "Use Output Tensor Type" self.USE_TOKEN_EMBEDDING_TYPE = "Use Token Embedding Type" self.KEEP_SPLIT = "Keep Split" self.KV_OVERRIDES = "KV Overrides:" self.ADD_NEW_OVERRIDE = "Add new override" self.QUANTIZE_MODEL = "Quantize Model" self.EXTRA_ARGUMENTS = "Extra Arguments:" self.EXTRA_ARGUMENTS_LABEL = "Additional command-line arguments" self.QUANTIZATION_COMMAND = "Quantization command" # Presets self.SAVE_PRESET = "Save Preset" self.LOAD_PRESET = "Load Preset" # Tasks self.TASKS = "Tasks:" # llama.cpp Download self.DOWNLOAD_LLAMACPP = "Download llama.cpp" self.SELECT_RELEASE = "Select Release:" self.SELECT_ASSET = "Select Asset:" self.EXTRACT_CUDA_FILES = "Extract CUDA files" self.SELECT_CUDA_BACKEND = "Select CUDA Backend:" self.DOWNLOAD = "Download" self.REFRESH_RELEASES = "Refresh Releases" # IMatrix Generation self.IMATRIX_GENERATION = "IMatrix Generation" self.DATA_FILE = "Data File:" self.MODEL = "Model:" self.OUTPUT = "Output:" self.OUTPUT_FREQUENCY = "Output Frequency:" self.GPU_OFFLOAD = "GPU Offload:" self.AUTO = "Auto" self.GENERATE_IMATRIX = "Generate IMatrix" self.CONTEXT_SIZE = "Context Size:" self.CONTEXT_SIZE_FOR_IMATRIX = "Context size for IMatrix generation" self.THREADS = "Threads:" self.NUMBER_OF_THREADS_FOR_IMATRIX = "Number of threads for IMatrix generation" self.IMATRIX_GENERATION_COMMAND = "IMatrix generation command" # LoRA Conversion self.LORA_CONVERSION = "LoRA Conversion" self.LORA_INPUT_PATH = "LoRA Input Path" self.LORA_OUTPUT_PATH = "LoRA Output Path" self.SELECT_LORA_INPUT_DIRECTORY = "Select LoRA Input Directory" self.SELECT_LORA_OUTPUT_FILE = "Select LoRA Output File" self.CONVERT_LORA = "Convert LoRA" self.LORA_CONVERSION_COMMAND = "LoRA conversion command" # LoRA Export self.EXPORT_LORA = "Export LoRA" self.GGML_LORA_ADAPTERS = "GGML LoRA Adapters" self.SELECT_LORA_ADAPTER_FILES = "Select LoRA Adapter Files" self.ADD_ADAPTER = "Add Adapter" self.DELETE_ADAPTER = "Delete" self.LORA_SCALE = "LoRA Scale" self.ENTER_LORA_SCALE_VALUE = "Enter LoRA Scale Value (Optional)" self.NUMBER_OF_THREADS_FOR_LORA_EXPORT = "Number of Threads for LoRA Export" self.LORA_EXPORT_COMMAND = "LoRA export command" # HuggingFace to GGUF Conversion self.HF_TO_GGUF_CONVERSION = "HuggingFace to GGUF Conversion" self.MODEL_DIRECTORY = "Model Directory:" self.OUTPUT_FILE = "Output File:" self.OUTPUT_TYPE = "Output Type:" self.VOCAB_ONLY = "Vocab Only" self.USE_TEMP_FILE = "Use Temp File" self.NO_LAZY_EVALUATION = "No Lazy Evaluation" self.MODEL_NAME = "Model Name:" self.VERBOSE = "Verbose" self.SPLIT_MAX_SIZE = "Split Max Size:" self.DRY_RUN = "Dry Run" self.CONVERT_HF_TO_GGUF = "Convert HF to GGUF" self.SELECT_HF_MODEL_DIRECTORY = "Select HuggingFace Model Directory" self.BROWSE_FOR_HF_MODEL_DIRECTORY = "Browsing for HuggingFace model directory" self.BROWSE_FOR_HF_TO_GGUF_OUTPUT = ( "Browsing for HuggingFace to GGUF output file" ) # Update Checking self.UPDATE_AVAILABLE = "Update Avaliable" self.NEW_VERSION_AVAILABLE = "A new version is avaliable: {}" self.DOWNLOAD_NEW_VERSION = "Download?" self.ERROR_CHECKING_FOR_UPDATES = "Error checking for updates:" self.CHECKING_FOR_UPDATES = "Checking for updates" # General Messages self.ERROR = "Error" self.WARNING = "Warning" self.PROPERTIES = "Properties" self.CANCEL = "Cancel" self.RESTART = "Restart" self.DELETE = "Delete" self.CONFIRM_DELETION = "Are you sure you want to delete this task?" self.TASK_RUNNING_WARNING = ( "Some tasks are still running. Are you sure you want to quit?" ) self.YES = "Yes" self.NO = "No" self.COMPLETED = "Completed" # File Types self.ALL_FILES = "All Files (*)" self.GGUF_FILES = "GGUF Files (*.gguf)" self.DAT_FILES = "DAT Files (*.dat)" self.JSON_FILES = "JSON Files (*.json)" self.BIN_FILES = "Binary Files (*.bin)" self.LORA_FILES = "LoRA Files (*.bin *.gguf)" self.GGUF_AND_BIN_FILES = "GGUF and Binary Files (*.gguf *.bin)" self.SHARDED = "sharded" # Status Messages self.DOWNLOAD_COMPLETE = "Download Complete" self.CUDA_EXTRACTION_FAILED = "CUDA Extraction Failed" self.PRESET_SAVED = "Preset Saved" self.PRESET_LOADED = "Preset Loaded" self.NO_ASSET_SELECTED = "No asset selected" self.DOWNLOAD_FAILED = "Download failed" self.NO_BACKEND_SELECTED = "No backend selected" self.NO_MODEL_SELECTED = "No model selected" self.NO_SUITABLE_CUDA_BACKENDS = "No suitable CUDA backends found" self.IN_PROGRESS = "In Progress" self.LLAMACPP_DOWNLOADED_EXTRACTED = ( "llama.cpp binary downloaded and extracted to {0}" ) self.CUDA_FILES_EXTRACTED = "CUDA files extracted to" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "No suitable CUDA backend found for extraction" ) self.ERROR_FETCHING_RELEASES = "Error fetching releases: {0}" self.CONFIRM_DELETION_TITLE = "Confirm Deletion" self.LOG_FOR = "Log for {0}" self.FAILED_TO_LOAD_PRESET = "Failed to load preset: {0}" self.INITIALIZING_AUTOGGUF = "Initializing AutoGGUF application" self.AUTOGGUF_INITIALIZATION_COMPLETE = "AutoGGUF initialization complete" self.REFRESHING_BACKENDS = "Refreshing backends" self.NO_BACKENDS_AVAILABLE = "No backends available" self.FOUND_VALID_BACKENDS = "Found {0} valid backends" self.SAVING_PRESET = "Saving preset" self.PRESET_SAVED_TO = "Preset saved to {0}" self.LOADING_PRESET = "Loading preset" self.PRESET_LOADED_FROM = "Preset loaded from {0}" self.ADDING_KV_OVERRIDE = "Adding KV override: {0}" self.SAVING_TASK_PRESET = "Saving task preset for {0}" self.TASK_PRESET_SAVED = "Task Preset Saved" self.TASK_PRESET_SAVED_TO = "Task preset saved to {0}" self.RESTARTING_TASK = "Restarting task: {0}" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "Download finished. Extracted to: {0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = ( "llama.cpp binary downloaded and extracted to {0}" ) self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "No suitable CUDA backend found for extraction" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "llama.cpp binary downloaded and extracted to {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "Refreshing llama.cpp releases" self.UPDATING_ASSET_LIST = "Updating asset list" self.UPDATING_CUDA_OPTIONS = "Updating CUDA options" self.STARTING_LLAMACPP_DOWNLOAD = "Starting llama.cpp download" self.UPDATING_CUDA_BACKENDS = "Updating CUDA backends" self.NO_CUDA_BACKEND_SELECTED = "No CUDA backend selected for extraction" self.EXTRACTING_CUDA_FILES = "Extracting CUDA files from {0} to {1}" self.DOWNLOAD_ERROR = "Download error: {0}" self.SHOWING_TASK_CONTEXT_MENU = "Showing task context menu" self.SHOWING_PROPERTIES_FOR_TASK = "Showing properties for task: {0}" self.CANCELLING_TASK = "Cancelling task: {0}" self.CANCELED = "Canceled" self.DELETING_TASK = "Deleting task: {0}" self.LOADING_MODELS = "Loading models" self.LOADED_MODELS = "Loaded {0} models" self.BROWSING_FOR_MODELS_DIRECTORY = "Browsing for models directory" self.SELECT_MODELS_DIRECTORY = "Select Models Directory" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Browsing for output directory" self.SELECT_OUTPUT_DIRECTORY = "Select Output Directory" self.BROWSING_FOR_LOGS_DIRECTORY = "Browsing for logs directory" self.SELECT_LOGS_DIRECTORY = "Select Logs Directory" self.BROWSING_FOR_IMATRIX_FILE = "Browsing for IMatrix file" self.SELECT_IMATRIX_FILE = "Select IMatrix File" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "CPU Usage: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "Validating quantization inputs" self.MODELS_PATH_REQUIRED = "Models path is required" self.OUTPUT_PATH_REQUIRED = "Output path is required" self.LOGS_PATH_REQUIRED = "Logs path is required" self.STARTING_MODEL_QUANTIZATION = "Starting model quantization" self.INPUT_FILE_NOT_EXIST = "Input file '{0}' does not exist." self.QUANTIZING_MODEL_TO = "Quantizing {0} to {1}" self.QUANTIZATION_TASK_STARTED = "Quantization task started for {0}" self.ERROR_STARTING_QUANTIZATION = "Error starting quantization: {0}" self.UPDATING_MODEL_INFO = "Updating model info: {0}" self.TASK_FINISHED = "Task finished: {0}" self.SHOWING_TASK_DETAILS_FOR = "Showing task details for: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "Browsing for IMatrix data file" self.SELECT_DATA_FILE = "Select Data File" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "Browsing for IMatrix model file" self.SELECT_MODEL_FILE = "Select Model File" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "Browsing for IMatrix output file" self.SELECT_OUTPUT_FILE = "Select Output File" self.STARTING_IMATRIX_GENERATION = "Starting IMatrix generation" self.BACKEND_PATH_NOT_EXIST = "Backend path does not exist: {0}" self.GENERATING_IMATRIX = "Generating IMatrix" self.ERROR_STARTING_IMATRIX_GENERATION = ( "Error starting IMatrix generation: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "IMatrix generation task started" self.ERROR_MESSAGE = "Error: {0}" self.TASK_ERROR = "Task error: {0}" self.APPLICATION_CLOSING = "Application closing" self.APPLICATION_CLOSED = "Application closed" self.SELECT_QUANTIZATION_TYPE = "Select the quantization type" self.ALLOWS_REQUANTIZING = ( "Allows requantizing tensors that have already been quantized" ) self.LEAVE_OUTPUT_WEIGHT = "Will leave output.weight un(re)quantized" self.DISABLE_K_QUANT_MIXTURES = ( "Disable k-quant mixtures and quantize all tensors to the same type" ) self.USE_DATA_AS_IMPORTANCE_MATRIX = ( "Use data in file as importance matrix for quant optimizations" ) self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Use importance matrix for these tensors" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Don't use importance matrix for these tensors" ) self.OUTPUT_TENSOR_TYPE = "Output Tensor Type:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Use this type for the output.weight tensor" ) self.TOKEN_EMBEDDING_TYPE = "Token Embedding Type:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Use this type for the token embeddings tensor" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "Will generate quantized model in the same shards as input" ) self.OVERRIDE_MODEL_METADATA = "Override model metadata" self.INPUT_DATA_FILE_FOR_IMATRIX = "Input data file for IMatrix generation" self.MODEL_TO_BE_QUANTIZED = "Model to be quantized" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = "Output path for the generated IMatrix" self.HOW_OFTEN_TO_SAVE_IMATRIX = "How often to save the IMatrix" self.SET_GPU_OFFLOAD_VALUE = "Set GPU offload value (-ngl)" self.STARTING_LORA_CONVERSION = "Starting LoRA Conversion" self.LORA_INPUT_PATH_REQUIRED = "LoRA input path is required." self.LORA_OUTPUT_PATH_REQUIRED = "LoRA output path is required." self.ERROR_STARTING_LORA_CONVERSION = "Error starting LoRA conversion: {}" self.LORA_CONVERSION_TASK_STARTED = "LoRA conversion task started." self.BROWSING_FOR_LORA_INPUT_DIRECTORY = "Browsing for LoRA input directory..." self.BROWSING_FOR_LORA_OUTPUT_FILE = "Browsing for LoRA output file..." self.CONVERTING_LORA = "LoRA Conversion" self.LORA_CONVERSION_FINISHED = "LoRA conversion finished." self.LORA_FILE_MOVED = "LoRA file moved from {} to {}." self.LORA_FILE_NOT_FOUND = "LoRA file not found: {}." self.ERROR_MOVING_LORA_FILE = "Error moving LoRA file: {}" self.MODEL_PATH_REQUIRED = "Model path is required." self.AT_LEAST_ONE_LORA_ADAPTER_REQUIRED = ( "At least one LoRA adapter is required." ) self.INVALID_LORA_SCALE_VALUE = "Invalid LoRA scale value." self.ERROR_STARTING_LORA_EXPORT = "Error starting LoRA export: {}" self.LORA_EXPORT_TASK_STARTED = "LoRA export task started." self.EXPORTING_LORA = "Exporting LoRA..." self.BROWSING_FOR_EXPORT_LORA_MODEL_FILE = ( "Browsing for Export LoRA Model File..." ) self.BROWSING_FOR_EXPORT_LORA_OUTPUT_FILE = ( "Browsing for Export LoRA Output File..." ) self.ADDING_LORA_ADAPTER = "Adding LoRA Adapter..." self.DELETING_LORA_ADAPTER = "Deleting LoRA Adapter..." self.SELECT_LORA_ADAPTER_FILE = "Select LoRA Adapter File" self.STARTING_LORA_EXPORT = "Starting LoRA export..." self.SELECT_OUTPUT_TYPE = "Select Output Type (GGUF or GGML)" self.BASE_MODEL = "Base Model" self.SELECT_BASE_MODEL_FILE = "Select Base Model File (GGUF)" self.BASE_MODEL_PATH_REQUIRED = "Base model path is required for GGUF output." self.BROWSING_FOR_BASE_MODEL_FILE = "Browsing for base model file..." self.SELECT_BASE_MODEL_FOLDER = ( "Select Base Model Folder (containing safetensors)" ) self.BROWSING_FOR_BASE_MODEL_FOLDER = "Browsing for base model folder..." self.LORA_CONVERSION_FROM_TO = "LoRA Conversion from {} to {}" self.GENERATING_IMATRIX_FOR = "Generating IMatrix for {}" self.MODEL_PATH_REQUIRED_FOR_IMATRIX = ( "Model path is required for IMatrix generation." ) self.NO_ASSET_SELECTED_FOR_CUDA_CHECK = "No asset selected for CUDA check" self.NO_QUANTIZATION_TYPE_SELECTED = "No quantization type selected. Please select at least one quantization type." self.STARTING_HF_TO_GGUF_CONVERSION = "Starting HuggingFace to GGUF conversion" self.MODEL_DIRECTORY_REQUIRED = "Model directory is required" self.HF_TO_GGUF_CONVERSION_COMMAND = "HF to GGUF Conversion Command: {}" self.CONVERTING_TO_GGUF = "Converting {} to GGUF" self.ERROR_STARTING_HF_TO_GGUF_CONVERSION = ( "Error starting HuggingFace to GGUF conversion: {}" ) self.HF_TO_GGUF_CONVERSION_TASK_STARTED = ( "HuggingFace to GGUF conversion task started" ) class _French(_Localization): def __init__(self): super().__init__() # Interface utilisateur générale self.WINDOW_TITLE = "AutoGGUF (quantificateur automatique de modèles GGUF)" self.RAM_USAGE = "Utilisation RAM :" self.CPU_USAGE = "Utilisation CPU :" self.BACKEND = "Backend Llama.cpp :" self.REFRESH_BACKENDS = "Actualiser les backends" self.MODELS_PATH = "Chemin des modèles :" self.OUTPUT_PATH = "Chemin de sortie :" self.LOGS_PATH = "Chemin des logs :" self.BROWSE = "Parcourir" self.AVAILABLE_MODELS = "Modèles disponibles :" self.REFRESH_MODELS = "Actualiser les modèles" # Importation de modèle self.IMPORT_MODEL = "Importer un modèle" self.SELECT_MODEL_TO_IMPORT = "Sélectionner le modèle à importer" self.CONFIRM_IMPORT = "Confirmer l'importation" self.IMPORT_MODEL_CONFIRMATION = "Voulez-vous importer le modèle {} ?" self.MODEL_IMPORTED_SUCCESSFULLY = "Modèle {} importé avec succès" self.IMPORTING_MODEL = "Importation du modèle" self.IMPORTED_MODEL_TOOLTIP = "Modèle importé : {}" # Vérification GGUF self.INVALID_GGUF_FILE = "Fichier GGUF invalide : {}" self.SHARDED_MODEL_NAME = "{} (Fragmenté)" self.CONCATENATED_FILE_WARNING = "C'est un fichier concaténé. Il ne fonctionnera pas avec llama-quantize ; veuillez d'abord concaténer le fichier." self.CONCATENATED_FILES_FOUND = "Trouvé {} parties de fichier concaténé. Veuillez d'abord concaténer les fichiers." # Surveillance GPU self.GPU_USAGE = "Utilisation GPU :" self.GPU_USAGE_FORMAT = "GPU : {:.1f}% | VRAM : {:.1f}% ({} Mo / {} Mo)" self.GPU_DETAILS = "Détails GPU" self.GPU_USAGE_OVER_TIME = "Utilisation GPU au fil du temps" self.VRAM_USAGE_OVER_TIME = "Utilisation VRAM au fil du temps" self.PERCENTAGE = "Pourcentage" self.TIME = "Temps (s)" self.NO_GPU_DETECTED = "Aucun GPU détecté" self.SELECT_GPU = "Sélectionner GPU" self.AMD_GPU_NOT_SUPPORTED = "GPU AMD détecté, mais non supporté" # Quantification self.QUANTIZATION_TYPE = "Type de quantification :" self.ALLOW_REQUANTIZE = "Autoriser la requantification" self.LEAVE_OUTPUT_TENSOR = "Laisser le tenseur de sortie" self.PURE = "Pur" self.IMATRIX = "IMatrix :" self.INCLUDE_WEIGHTS = "Inclure les poids :" self.EXCLUDE_WEIGHTS = "Exclure les poids :" self.USE_OUTPUT_TENSOR_TYPE = "Utiliser le type de tenseur de sortie" self.USE_TOKEN_EMBEDDING_TYPE = "Utiliser le type d'intégration de token" self.KEEP_SPLIT = "Garder la séparation" self.KV_OVERRIDES = "Substitutions KV :" self.ADD_NEW_OVERRIDE = "Ajouter une nouvelle substitution" self.QUANTIZE_MODEL = "Quantifier le modèle" self.EXTRA_ARGUMENTS = "Arguments supplémentaires :" self.EXTRA_ARGUMENTS_LABEL = "Arguments de ligne de commande supplémentaires" self.QUANTIZATION_COMMAND = "Commande de quantification" # Préréglages self.SAVE_PRESET = "Sauvegarder le préréglage" self.LOAD_PRESET = "Charger le préréglage" # Tâches self.TASKS = "Tâches :" # Téléchargement llama.cpp self.DOWNLOAD_LLAMACPP = "Télécharger llama.cpp" self.SELECT_RELEASE = "Sélectionner la version :" self.SELECT_ASSET = "Sélectionner l'asset :" self.EXTRACT_CUDA_FILES = "Extraire les fichiers CUDA" self.SELECT_CUDA_BACKEND = "Sélectionner le backend CUDA :" self.DOWNLOAD = "Télécharger" self.REFRESH_RELEASES = "Actualiser les versions" # Génération IMatrix self.IMATRIX_GENERATION = "Génération IMatrix" self.DATA_FILE = "Fichier de données :" self.MODEL = "Modèle :" self.OUTPUT = "Sortie :" self.OUTPUT_FREQUENCY = "Fréquence de sortie :" self.GPU_OFFLOAD = "Déchargement GPU :" self.AUTO = "Auto" self.GENERATE_IMATRIX = "Générer IMatrix" self.CONTEXT_SIZE = "Taille du contexte :" self.CONTEXT_SIZE_FOR_IMATRIX = "Taille du contexte pour la génération IMatrix" self.THREADS = "Threads :" self.NUMBER_OF_THREADS_FOR_IMATRIX = ( "Nombre de threads pour la génération IMatrix" ) self.IMATRIX_GENERATION_COMMAND = "Commande de génération IMatrix" # Conversion LoRA self.LORA_CONVERSION = "Conversion LoRA" self.LORA_INPUT_PATH = "Chemin d'entrée LoRA" self.LORA_OUTPUT_PATH = "Chemin de sortie LoRA" self.SELECT_LORA_INPUT_DIRECTORY = "Sélectionner le répertoire d'entrée LoRA" self.SELECT_LORA_OUTPUT_FILE = "Sélectionner le fichier de sortie LoRA" self.CONVERT_LORA = "Convertir LoRA" self.LORA_CONVERSION_COMMAND = "Commande de conversion LoRA" # Exportation LoRA self.EXPORT_LORA = "Exporter LoRA" self.GGML_LORA_ADAPTERS = "Adaptateurs LoRA GGML" self.SELECT_LORA_ADAPTER_FILES = "Sélectionner les fichiers d'adaptateur LoRA" self.ADD_ADAPTER = "Ajouter un adaptateur" self.DELETE_ADAPTER = "Supprimer" self.LORA_SCALE = "Échelle LoRA" self.ENTER_LORA_SCALE_VALUE = "Entrer la valeur d'échelle LoRA (Optionnel)" self.NUMBER_OF_THREADS_FOR_LORA_EXPORT = ( "Nombre de threads pour l'exportation LoRA" ) self.LORA_EXPORT_COMMAND = "Commande d'exportation LoRA" # Conversion HuggingFace vers GGUF self.HF_TO_GGUF_CONVERSION = "Conversion HuggingFace vers GGUF" self.MODEL_DIRECTORY = "Répertoire du modèle :" self.OUTPUT_FILE = "Fichier de sortie :" self.OUTPUT_TYPE = "Type de sortie :" self.VOCAB_ONLY = "Vocabulaire uniquement" self.USE_TEMP_FILE = "Utiliser un fichier temporaire" self.NO_LAZY_EVALUATION = "Pas d'évaluation paresseuse" self.MODEL_NAME = "Nom du modèle :" self.VERBOSE = "Verbeux" self.SPLIT_MAX_SIZE = "Taille max de division :" self.DRY_RUN = "Exécution à blanc" self.CONVERT_HF_TO_GGUF = "Convertir HF vers GGUF" self.SELECT_HF_MODEL_DIRECTORY = ( "Sélectionner le répertoire du modèle HuggingFace" ) self.BROWSE_FOR_HF_MODEL_DIRECTORY = ( "Parcourir pour le répertoire du modèle HuggingFace" ) self.BROWSE_FOR_HF_TO_GGUF_OUTPUT = ( "Parcourir pour le fichier de sortie HuggingFace vers GGUF" ) # Vérification des mises à jour self.UPDATE_AVAILABLE = "Mise à jour disponible" self.NEW_VERSION_AVAILABLE = "Une nouvelle version est disponible : {}" self.DOWNLOAD_NEW_VERSION = "Télécharger ?" self.ERROR_CHECKING_FOR_UPDATES = ( "Erreur lors de la vérification des mises à jour :" ) self.CHECKING_FOR_UPDATES = "Vérification des mises à jour" # Messages généraux self.ERROR = "Erreur" self.WARNING = "Avertissement" self.PROPERTIES = "Propriétés" self.CANCEL = "Annuler" self.RESTART = "Redémarrer" self.DELETE = "Supprimer" self.CONFIRM_DELETION = "Êtes-vous sûr de vouloir supprimer cette tâche ?" self.TASK_RUNNING_WARNING = ( "Certaines tâches sont encore en cours. Êtes-vous sûr de vouloir quitter ?" ) self.YES = "Oui" self.NO = "Non" self.COMPLETED = "Terminé" # Types de fichiers self.ALL_FILES = "Tous les fichiers (*)" self.GGUF_FILES = "Fichiers GGUF (*.gguf)" self.DAT_FILES = "Fichiers DAT (*.dat)" self.JSON_FILES = "Fichiers JSON (*.json)" self.BIN_FILES = "Fichiers binaires (*.bin)" self.LORA_FILES = "Fichiers LoRA (*.bin *.gguf)" self.GGUF_AND_BIN_FILES = "Fichiers GGUF et binaires (*.gguf *.bin)" self.SHARDED = "fragmenté" # Messages d'état self.DOWNLOAD_COMPLETE = "Téléchargement terminé" self.CUDA_EXTRACTION_FAILED = "Échec de l'extraction CUDA" self.PRESET_SAVED = "Préréglage sauvegardé" self.PRESET_LOADED = "Préréglage chargé" self.NO_ASSET_SELECTED = "Aucun asset sélectionné" self.DOWNLOAD_FAILED = "Échec du téléchargement" self.NO_BACKEND_SELECTED = "Aucun backend sélectionné" self.NO_MODEL_SELECTED = "Aucun modèle sélectionné" self.NO_SUITABLE_CUDA_BACKENDS = "Aucun backend CUDA approprié trouvé" self.IN_PROGRESS = "En cours" self.LLAMACPP_DOWNLOADED_EXTRACTED = ( "Binaire llama.cpp téléchargé et extrait dans {0}" ) self.CUDA_FILES_EXTRACTED = "Fichiers CUDA extraits dans" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "Aucun backend CUDA approprié trouvé pour l'extraction" ) self.ERROR_FETCHING_RELEASES = ( "Erreur lors de la récupération des versions : {0}" ) self.CONFIRM_DELETION_TITLE = "Confirmer la suppression" self.LOG_FOR = "Log pour {0}" self.FAILED_TO_LOAD_PRESET = "Échec du chargement du préréglage : {0}" self.INITIALIZING_AUTOGGUF = "Initialisation de l'application AutoGGUF" self.AUTOGGUF_INITIALIZATION_COMPLETE = "Initialisation d'AutoGGUF terminée" self.REFRESHING_BACKENDS = "Actualisation des backends" self.NO_BACKENDS_AVAILABLE = "Aucun backend disponible" self.FOUND_VALID_BACKENDS = "Trouvé {0} backends valides" self.SAVING_PRESET = "Sauvegarde du préréglage" self.PRESET_SAVED_TO = "Préréglage sauvegardé dans {0}" self.LOADING_PRESET = "Chargement du préréglage" self.PRESET_LOADED_FROM = "Préréglage chargé depuis {0}" self.ADDING_KV_OVERRIDE = "Ajout de la substitution KV : {0}" self.SAVING_TASK_PRESET = "Sauvegarde du préréglage de tâche pour {0}" self.TASK_PRESET_SAVED = "Préréglage de tâche sauvegardé" self.TASK_PRESET_SAVED_TO = "Préréglage de tâche sauvegardé dans {0}" self.RESTARTING_TASK = "Redémarrage de la tâche : {0}" self.DOWNLOAD_FINISHED_EXTRACTED_TO = ( "Téléchargement terminé. Extrait dans : {0}" ) self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = ( "Binaire llama.cpp téléchargé et extrait dans {0}" ) self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "Aucun backend CUDA approprié trouvé pour l'extraction" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "Binaire llama.cpp téléchargé et extrait dans {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "Actualisation des versions llama.cpp" self.UPDATING_ASSET_LIST = "Mise à jour de la liste des assets" self.UPDATING_CUDA_OPTIONS = "Mise à jour des options CUDA" self.STARTING_LLAMACPP_DOWNLOAD = "Démarrage du téléchargement de llama.cpp" self.UPDATING_CUDA_BACKENDS = "Mise à jour des backends CUDA" self.NO_CUDA_BACKEND_SELECTED = ( "Aucun backend CUDA sélectionné pour l'extraction" ) self.EXTRACTING_CUDA_FILES = "Extraction des fichiers CUDA de {0} vers {1}" self.DOWNLOAD_ERROR = "Erreur de téléchargement : {0}" self.SHOWING_TASK_CONTEXT_MENU = "Affichage du menu contextuel de la tâche" self.SHOWING_PROPERTIES_FOR_TASK = ( "Affichage des propriétés pour la tâche : {0}" ) self.CANCELLING_TASK = "Annulation de la tâche : {0}" self.CANCELED = "Annulé" self.DELETING_TASK = "Suppression de la tâche : {0}" self.LOADING_MODELS = "Chargement des modèles" self.LOADED_MODELS = "Chargé {0} modèles" self.BROWSING_FOR_MODELS_DIRECTORY = "Parcourir pour le répertoire des modèles" self.SELECT_MODELS_DIRECTORY = "Sélectionner le répertoire des modèles" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Parcourir pour le répertoire de sortie" self.SELECT_OUTPUT_DIRECTORY = "Sélectionner le répertoire de sortie" self.BROWSING_FOR_LOGS_DIRECTORY = "Parcourir pour le répertoire des logs" self.SELECT_LOGS_DIRECTORY = "Sélectionner le répertoire des logs" self.BROWSING_FOR_IMATRIX_FILE = "Parcourir pour le fichier IMatrix" self.SELECT_IMATRIX_FILE = "Sélectionner le fichier IMatrix" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} Mo / {2} Mo)" self.CPU_USAGE_FORMAT = "Utilisation CPU : {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "Validation des entrées de quantification" self.MODELS_PATH_REQUIRED = "Le chemin des modèles est requis" self.OUTPUT_PATH_REQUIRED = "Le chemin de sortie est requis" self.LOGS_PATH_REQUIRED = "Le chemin des logs est requis" self.STARTING_MODEL_QUANTIZATION = "Démarrage de la quantification du modèle" self.INPUT_FILE_NOT_EXIST = "Le fichier d'entrée '{0}' n'existe pas." self.QUANTIZING_MODEL_TO = "Quantification de {0} vers {1}" self.QUANTIZATION_TASK_STARTED = "Tâche de quantification démarrée pour {0}" self.ERROR_STARTING_QUANTIZATION = ( "Erreur au démarrage de la quantification : {0}" ) self.UPDATING_MODEL_INFO = "Mise à jour des informations du modèle : {0}" self.TASK_FINISHED = "Tâche terminée : {0}" self.SHOWING_TASK_DETAILS_FOR = "Affichage des détails de la tâche pour : {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = ( "Parcourir pour le fichier de données IMatrix" ) self.SELECT_DATA_FILE = "Sélectionner le fichier de données" self.BROWSING_FOR_IMATRIX_MODEL_FILE = ( "Parcourir pour le fichier de modèle IMatrix" ) self.SELECT_MODEL_FILE = "Sélectionner le fichier de modèle" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = ( "Parcourir pour le fichier de sortie IMatrix" ) self.SELECT_OUTPUT_FILE = "Sélectionner le fichier de sortie" self.STARTING_IMATRIX_GENERATION = "Démarrage de la génération IMatrix" self.BACKEND_PATH_NOT_EXIST = "Le chemin du backend n'existe pas : {0}" self.GENERATING_IMATRIX = "Génération de l'IMatrix" self.ERROR_STARTING_IMATRIX_GENERATION = ( "Erreur au démarrage de la génération IMatrix : {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "Tâche de génération IMatrix démarrée" self.ERROR_MESSAGE = "Erreur : {0}" self.TASK_ERROR = "Erreur de tâche : {0}" self.APPLICATION_CLOSING = "Fermeture de l'application" self.APPLICATION_CLOSED = "Application fermée" self.SELECT_QUANTIZATION_TYPE = "Sélectionner le type de quantification" self.ALLOWS_REQUANTIZING = "Permet de requantifier les tenseurs déjà quantifiés" self.LEAVE_OUTPUT_WEIGHT = "Laissera output.weight non (re)quantifié" self.DISABLE_K_QUANT_MIXTURES = "Désactiver les mélanges k-quant et quantifier tous les tenseurs au même type" self.USE_DATA_AS_IMPORTANCE_MATRIX = "Utiliser les données du fichier comme matrice d'importance pour les optimisations de quantification" self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Utiliser la matrice d'importance pour ces tenseurs" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Ne pas utiliser la matrice d'importance pour ces tenseurs" ) self.OUTPUT_TENSOR_TYPE = "Type de tenseur de sortie :" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Utiliser ce type pour le tenseur output.weight" ) self.TOKEN_EMBEDDING_TYPE = "Type d'intégration de token :" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Utiliser ce type pour le tenseur d'intégrations de tokens" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "Générera le modèle quantifié dans les mêmes fragments que l'entrée" ) self.OVERRIDE_MODEL_METADATA = "Remplacer les métadonnées du modèle" self.INPUT_DATA_FILE_FOR_IMATRIX = ( "Fichier de données d'entrée pour la génération IMatrix" ) self.MODEL_TO_BE_QUANTIZED = "Modèle à quantifier" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = ( "Chemin de sortie pour l'IMatrix généré" ) self.HOW_OFTEN_TO_SAVE_IMATRIX = "Fréquence de sauvegarde de l'IMatrix" self.SET_GPU_OFFLOAD_VALUE = "Définir la valeur de déchargement GPU (-ngl)" self.STARTING_LORA_CONVERSION = "Démarrage de la conversion LoRA" self.LORA_INPUT_PATH_REQUIRED = "Le chemin d'entrée LoRA est requis." self.LORA_OUTPUT_PATH_REQUIRED = "Le chemin de sortie LoRA est requis." self.ERROR_STARTING_LORA_CONVERSION = ( "Erreur au démarrage de la conversion LoRA : {}" ) self.LORA_CONVERSION_TASK_STARTED = "Tâche de conversion LoRA démarrée." self.BROWSING_FOR_LORA_INPUT_DIRECTORY = ( "Parcourir pour le répertoire d'entrée LoRA..." ) self.BROWSING_FOR_LORA_OUTPUT_FILE = ( "Parcourir pour le fichier de sortie LoRA..." ) self.CONVERTING_LORA = "Conversion LoRA" self.LORA_CONVERSION_FINISHED = "Conversion LoRA terminée." self.LORA_FILE_MOVED = "Fichier LoRA déplacé de {} vers {}." self.LORA_FILE_NOT_FOUND = "Fichier LoRA non trouvé : {}." self.ERROR_MOVING_LORA_FILE = "Erreur lors du déplacement du fichier LoRA : {}" self.MODEL_PATH_REQUIRED = "Le chemin du modèle est requis." self.AT_LEAST_ONE_LORA_ADAPTER_REQUIRED = ( "Au moins un adaptateur LoRA est requis." ) self.INVALID_LORA_SCALE_VALUE = "Valeur d'échelle LoRA invalide." self.ERROR_STARTING_LORA_EXPORT = ( "Erreur au démarrage de l'exportation LoRA : {}" ) self.LORA_EXPORT_TASK_STARTED = "Tâche d'exportation LoRA démarrée." self.EXPORTING_LORA = "Exportation LoRA..." self.BROWSING_FOR_EXPORT_LORA_MODEL_FILE = ( "Parcourir pour le fichier de modèle d'exportation LoRA..." ) self.BROWSING_FOR_EXPORT_LORA_OUTPUT_FILE = ( "Parcourir pour le fichier de sortie d'exportation LoRA..." ) self.ADDING_LORA_ADAPTER = "Ajout d'un adaptateur LoRA..." self.DELETING_LORA_ADAPTER = "Suppression d'un adaptateur LoRA..." self.SELECT_LORA_ADAPTER_FILE = "Sélectionner le fichier d'adaptateur LoRA" self.STARTING_LORA_EXPORT = "Démarrage de l'exportation LoRA..." self.SELECT_OUTPUT_TYPE = "Sélectionner le type de sortie (GGUF ou GGML)" self.BASE_MODEL = "Modèle de base" self.SELECT_BASE_MODEL_FILE = "Sélectionner le fichier de modèle de base (GGUF)" self.BASE_MODEL_PATH_REQUIRED = ( "Le chemin du modèle de base est requis pour la sortie GGUF." ) self.BROWSING_FOR_BASE_MODEL_FILE = ( "Parcourir pour le fichier de modèle de base..." ) self.SELECT_BASE_MODEL_FOLDER = ( "Sélectionner le dossier du modèle de base (contenant safetensors)" ) self.BROWSING_FOR_BASE_MODEL_FOLDER = ( "Parcourir pour le dossier du modèle de base..." ) self.LORA_CONVERSION_FROM_TO = "Conversion LoRA de {} vers {}" self.GENERATING_IMATRIX_FOR = "Génération IMatrix pour {}" self.MODEL_PATH_REQUIRED_FOR_IMATRIX = ( "Le chemin du modèle est requis pour la génération IMatrix." ) self.NO_ASSET_SELECTED_FOR_CUDA_CHECK = ( "Aucun asset sélectionné pour la vérification CUDA" ) self.NO_QUANTIZATION_TYPE_SELECTED = "Aucun type de quantification sélectionné. Veuillez sélectionner au moins un type de quantification." self.STARTING_HF_TO_GGUF_CONVERSION = ( "Démarrage de la conversion HuggingFace vers GGUF" ) self.MODEL_DIRECTORY_REQUIRED = "Le répertoire du modèle est requis" self.HF_TO_GGUF_CONVERSION_COMMAND = "Commande de conversion HF vers GGUF : {}" self.CONVERTING_TO_GGUF = "Conversion de {} vers GGUF" self.ERROR_STARTING_HF_TO_GGUF_CONVERSION = ( "Erreur au démarrage de la conversion HuggingFace vers GGUF : {}" ) self.HF_TO_GGUF_CONVERSION_TASK_STARTED = ( "Tâche de conversion HuggingFace vers GGUF démarrée" ) class _SimplifiedChinese(_Localization): def __init__(self): super().__init__() # 通用界面 self.WINDOW_TITLE = "AutoGGUF(自动GGUF模型量化器)" self.RAM_USAGE = "内存使用率:" self.CPU_USAGE = "CPU使用率:" self.BACKEND = "Llama.cpp后端:" self.REFRESH_BACKENDS = "刷新后端" self.MODELS_PATH = "模型路径:" self.OUTPUT_PATH = "输出路径:" self.LOGS_PATH = "日志路径:" self.BROWSE = "浏览" self.AVAILABLE_MODELS = "可用模型:" self.REFRESH_MODELS = "刷新模型" # 量化 self.QUANTIZATION_TYPE = "量化类型:" self.ALLOW_REQUANTIZE = "允许重新量化" self.LEAVE_OUTPUT_TENSOR = "保留输出张量" self.PURE = "纯净" self.IMATRIX = "重要性矩阵:" self.INCLUDE_WEIGHTS = "包含权重:" self.EXCLUDE_WEIGHTS = "排除权重:" self.USE_OUTPUT_TENSOR_TYPE = "使用输出张量类型" self.USE_TOKEN_EMBEDDING_TYPE = "使用词元嵌入类型" self.KEEP_SPLIT = "保持分割" self.KV_OVERRIDES = "KV覆盖:" self.ADD_NEW_OVERRIDE = "添加新覆盖" self.QUANTIZE_MODEL = "量化模型" self.EXTRA_ARGUMENTS = "额外参数:" self.EXTRA_ARGUMENTS_LABEL = "附加命令行参数" self.QUANTIZATION_COMMAND = "量化命令" # 预设 self.SAVE_PRESET = "保存预设" self.LOAD_PRESET = "加载预设" # 任务 self.TASKS = "任务:" # llama.cpp下载 self.DOWNLOAD_LLAMACPP = "下载llama.cpp" self.SELECT_RELEASE = "选择版本:" self.SELECT_ASSET = "选择资源:" self.EXTRACT_CUDA_FILES = "提取CUDA文件" self.SELECT_CUDA_BACKEND = "选择CUDA后端:" self.DOWNLOAD = "下载" self.REFRESH_RELEASES = "刷新版本" # IMatrix生成 self.IMATRIX_GENERATION = "IMatrix生成" self.DATA_FILE = "数据文件:" self.MODEL = "模型:" self.OUTPUT = "输出:" self.OUTPUT_FREQUENCY = "输出频率:" self.GPU_OFFLOAD = "GPU卸载:" self.AUTO = "自动" self.GENERATE_IMATRIX = "生成IMatrix" self.CONTEXT_SIZE = "上下文大小:" self.CONTEXT_SIZE_FOR_IMATRIX = "IMatrix生成的上下文大小" self.THREADS = "线程数:" self.NUMBER_OF_THREADS_FOR_IMATRIX = "IMatrix生成的线程数" self.IMATRIX_GENERATION_COMMAND = "IMatrix生成命令" # LoRA转换 self.LORA_CONVERSION = "LoRA转换" self.LORA_INPUT_PATH = "LoRA输入路径" self.LORA_OUTPUT_PATH = "LoRA输出路径" self.SELECT_LORA_INPUT_DIRECTORY = "选择LoRA输入目录" self.SELECT_LORA_OUTPUT_FILE = "选择LoRA输出文件" self.CONVERT_LORA = "转换LoRA" self.LORA_CONVERSION_COMMAND = "LoRA转换命令" # LoRA导出 self.EXPORT_LORA = "导出LoRA" self.GGML_LORA_ADAPTERS = "GGML LoRA适配器" self.SELECT_LORA_ADAPTER_FILES = "选择LoRA适配器文件" self.ADD_ADAPTER = "添加适配器" self.DELETE_ADAPTER = "删除" self.LORA_SCALE = "LoRA比例" self.ENTER_LORA_SCALE_VALUE = "输入LoRA比例值(可选)" self.NUMBER_OF_THREADS_FOR_LORA_EXPORT = "LoRA导出的线程数" self.LORA_EXPORT_COMMAND = "LoRA导出命令" # HuggingFace到GGUF转换 self.HF_TO_GGUF_CONVERSION = "HuggingFace到GGUF转换" self.MODEL_DIRECTORY = "模型目录:" self.OUTPUT_FILE = "输出文件:" self.OUTPUT_TYPE = "输出类型:" self.VOCAB_ONLY = "仅词汇表" self.USE_TEMP_FILE = "使用临时文件" self.NO_LAZY_EVALUATION = "不使用延迟评估" self.MODEL_NAME = "模型名称:" self.VERBOSE = "详细模式" self.SPLIT_MAX_SIZE = "最大分割大小:" self.DRY_RUN = "试运行" self.CONVERT_HF_TO_GGUF = "转换HF到GGUF" self.SELECT_HF_MODEL_DIRECTORY = "选择HuggingFace模型目录" self.BROWSE_FOR_HF_MODEL_DIRECTORY = "浏览HuggingFace模型目录" self.BROWSE_FOR_HF_TO_GGUF_OUTPUT = "浏览HuggingFace到GGUF输出文件" # 通用消息 self.ERROR = "错误" self.WARNING = "警告" self.PROPERTIES = "属性" self.CANCEL = "取消" self.RESTART = "重启" self.DELETE = "删除" self.CONFIRM_DELETION = "您确定要删除此任务吗?" self.TASK_RUNNING_WARNING = "一些任务仍在运行。您确定要退出吗?" self.YES = "是" self.NO = "否" self.COMPLETED = "已完成" # 文件类型 self.ALL_FILES = "所有文件 (*)" self.GGUF_FILES = "GGUF文件 (*.gguf)" self.DAT_FILES = "DAT文件 (*.dat)" self.JSON_FILES = "JSON文件 (*.json)" self.BIN_FILES = "二进制文件 (*.bin)" self.LORA_FILES = "LoRA文件 (*.bin)" self.GGUF_AND_BIN_FILES = "GGUF和二进制文件 (*.gguf *.bin)" self.SHARDED = "分片" # 状态消息 self.DOWNLOAD_COMPLETE = "下载完成" self.CUDA_EXTRACTION_FAILED = "CUDA提取失败" self.PRESET_SAVED = "预设已保存" self.PRESET_LOADED = "预设已加载" self.NO_ASSET_SELECTED = "未选择资源" self.DOWNLOAD_FAILED = "下载失败" self.NO_BACKEND_SELECTED = "未选择后端" self.NO_MODEL_SELECTED = "未选择模型" self.NO_SUITABLE_CUDA_BACKENDS = "未找到合适的CUDA后端" self.IN_PROGRESS = "进行中" self.LLAMACPP_DOWNLOADED_EXTRACTED = "llama.cpp二进制文件已下载并解压到{0}" self.CUDA_FILES_EXTRACTED = "CUDA文件已提取到" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = "未找到合适的CUDA后端进行提取" self.ERROR_FETCHING_RELEASES = "获取版本时出错:{0}" self.CONFIRM_DELETION_TITLE = "确认删除" self.LOG_FOR = "{0}的日志" self.FAILED_LOAD_PRESET = "加载预设失败:{0}" self.INITIALIZING_AUTOGGUF = "初始化AutoGGUF应用程序" self.AUTOGGUF_INITIALIZATION_COMPLETE = "AutoGGUF初始化完成" self.REFRESHING_BACKENDS = "刷新后端" self.NO_BACKENDS_AVAILABLE = "没有可用的后端" self.FOUND_VALID_BACKENDS = "找到{0}个有效后端" self.SAVING_PRESET = "保存预设" self.PRESET_SAVED_TO = "预设已保存到{0}" self.LOADING_PRESET = "加载预设" self.PRESET_LOADED_FROM = "预设已从{0}加载" self.ADDING_KV_OVERRIDE = "添加KV覆盖:{0}" self.SAVING_TASK_PRESET = "保存{0}的任务预设" self.TASK_PRESET_SAVED = "任务预设已保存" self.TASK_PRESET_SAVED_TO = "任务预设已保存到{0}" self.RESTARTING_TASK = "重启任务:{0}" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "下载完成。已解压到:{0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "llama.cpp二进制文件已下载并解压到{0}" self.NO_SUITABLE_CUDA_BACKEND_FOUND = "未找到合适的CUDA后端进行提取" self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "llama.cpp二进制文件已下载并解压到{0}" ) self.REFRESHING_LLAMACPP_RELEASES = "刷新llama.cpp版本" self.UPDATING_ASSET_LIST = "更新资源列表" self.UPDATING_CUDA_OPTIONS = "更新CUDA选项" self.STARTING_LLAMACPP_DOWNLOAD = "开始下载llama.cpp" self.UPDATING_CUDA_BACKENDS = "更新CUDA后端" self.NO_CUDA_BACKEND_SELECTED = "未选择CUDA后端进行提取" self.EXTRACTING_CUDA_FILES = "从{0}提取CUDA文件到{1}" self.DOWNLOAD_ERROR = "下载错误:{0}" self.SHOWING_TASK_CONTEXT_MENU = "显示任务上下文菜单" self.SHOWING_PROPERTIES_FOR_TASK = "显示任务属性:{0}" self.CANCELLING_TASK = "取消任务:{0}" self.CANCELED = "已取消" self.DELETING_TASK = "删除任务:{0}" self.LOADING_MODELS = "加载模型" self.LOADED_MODELS = "已加载{0}个模型" self.BROWSING_FOR_MODELS_DIRECTORY = "浏览模型目录" self.SELECT_MODELS_DIRECTORY = "选择模型目录" self.BROWSING_FOR_OUTPUT_DIRECTORY = "浏览输出目录" self.SELECT_OUTPUT_DIRECTORY = "选择输出目录" self.BROWSING_FOR_LOGS_DIRECTORY = "浏览日志目录" self.SELECT_LOGS_DIRECTORY = "选择日志目录" self.BROWSING_FOR_IMATRIX_FILE = "浏览IMatrix文件" self.SELECT_IMATRIX_FILE = "选择IMatrix文件" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "CPU使用率:{0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "验证量化输入" self.MODELS_PATH_REQUIRED = "需要模型路径" self.OUTPUT_PATH_REQUIRED = "需要输出路径" self.LOGS_PATH_REQUIRED = "需要日志路径" self.STARTING_MODEL_QUANTIZATION = "开始模型量化" self.INPUT_FILE_NOT_EXIST = "输入文件'{0}'不存在。" self.QUANTIZING_MODEL_TO = "将{0}量化为{1}" self.QUANTIZATION_TASK_STARTED = "已开始{0}的量化任务" self.ERROR_STARTING_QUANTIZATION = "启动量化时出错:{0}" self.UPDATING_MODEL_INFO = "更新模型信息:{0}" self.TASK_FINISHED = "任务完成:{0}" self.SHOWING_TASK_DETAILS_FOR = "显示任务详情:{0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "浏览IMatrix数据文件" self.SELECT_DATA_FILE = "选择数据文件" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "浏览IMatrix模型文件" self.SELECT_MODEL_FILE = "选择模型文件" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "浏览IMatrix输出文件" self.SELECT_OUTPUT_FILE = "选择输出文件" self.STARTING_IMATRIX_GENERATION = "开始IMatrix生成" self.BACKEND_PATH_NOT_EXIST = "后端路径不存在:{0}" self.GENERATING_IMATRIX = "生成IMatrix" self.ERROR_STARTING_IMATRIX_GENERATION = "启动IMatrix生成时出错:{0}" self.IMATRIX_GENERATION_TASK_STARTED = "IMatrix生成任务已开始" self.ERROR_MESSAGE = "错误:{0}" self.TASK_ERROR = "任务错误:{0}" self.APPLICATION_CLOSING = "应用程序正在关闭" self.APPLICATION_CLOSED = "应用程序已关闭" self.SELECT_QUANTIZATION_TYPE = "选择量化类型" self.ALLOWS_REQUANTIZING = "允许重新量化已量化的张量" self.LEAVE_OUTPUT_WEIGHT = "将保持output.weight不被(重新)量化" self.DISABLE_K_QUANT_MIXTURES = "禁用k-quant混合并将所有张量量化为相同类型" self.USE_DATA_AS_IMPORTANCE_MATRIX = "使用文件中的数据作为量化优化的重要性矩阵" self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = "对这些张量使用重要性矩阵" self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = "不对这些张量使用重要性矩阵" self.OUTPUT_TENSOR_TYPE = "输出张量类型:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = "对output.weight张量使用此类型" self.TOKEN_EMBEDDING_TYPE = "词元嵌入类型:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = "对词元嵌入张量使用此类型" self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "将生成与输入相同分片的量化模型" ) self.OVERRIDE_MODEL_METADATA = "覆盖模型元数据" self.INPUT_DATA_FILE_FOR_IMATRIX = "IMatrix生成的输入数据文件" self.MODEL_TO_BE_QUANTIZED = "要量化的模型" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = "生成的IMatrix的输出路径" self.HOW_OFTEN_TO_SAVE_IMATRIX = "保存IMatrix的频率" self.SET_GPU_OFFLOAD_VALUE = "设置GPU卸载值(-ngl)" self.STARTING_LORA_CONVERSION = "开始LoRA转换" self.LORA_INPUT_PATH_REQUIRED = "需要LoRA输入路径。" self.LORA_OUTPUT_PATH_REQUIRED = "需要LoRA输出路径。" self.ERROR_STARTING_LORA_CONVERSION = "启动LoRA转换时出错:{}" self.LORA_CONVERSION_TASK_STARTED = "LoRA转换任务已开始。" self.BROWSING_FOR_LORA_INPUT_DIRECTORY = "浏览LoRA输入目录..." self.BROWSING_FOR_LORA_OUTPUT_FILE = "浏览LoRA输出文件..." self.CONVERTING_LORA = "LoRA转换" self.LORA_CONVERSION_FINISHED = "LoRA转换完成。" self.LORA_FILE_MOVED = "LoRA文件已从{}移动到{}。" self.LORA_FILE_NOT_FOUND = "未找到LoRA文件:{}。" self.ERROR_MOVING_LORA_FILE = "移动LoRA文件时出错:{}" self.MODEL_PATH_REQUIRED = "需要模型路径。" self.AT_LEAST_ONE_LORA_ADAPTER_REQUIRED = "至少需要一个LoRA适配器。" self.INVALID_LORA_SCALE_VALUE = "无效的LoRA比例值。" self.ERROR_STARTING_LORA_EXPORT = "启动LoRA导出时出错:{}" self.LORA_EXPORT_TASK_STARTED = "LoRA导出任务已开始。" self.EXPORTING_LORA = "导出LoRA..." self.BROWSING_FOR_EXPORT_LORA_MODEL_FILE = "浏览导出LoRA模型文件..." self.BROWSING_FOR_EXPORT_LORA_OUTPUT_FILE = "浏览导出LoRA输出文件..." self.ADDING_LORA_ADAPTER = "添加LoRA适配器..." self.DELETING_LORA_ADAPTER = "删除LoRA适配器..." self.SELECT_LORA_ADAPTER_FILE = "选择LoRA适配器文件" self.STARTING_LORA_EXPORT = "开始LoRA导出..." self.SELECT_OUTPUT_TYPE = "选择输出类型(GGUF或GGML)" self.BASE_MODEL = "基础模型" self.SELECT_BASE_MODEL_FILE = "选择基础模型文件(GGUF)" self.BASE_MODEL_PATH_REQUIRED = "GGUF输出需要基础模型路径。" self.BROWSING_FOR_BASE_MODEL_FILE = "浏览基础模型文件..." self.SELECT_BASE_MODEL_FOLDER = "选择基础模型文件夹(包含safetensors)" self.BROWSING_FOR_BASE_MODEL_FOLDER = "浏览基础模型文件夹..." self.LORA_CONVERSION_FROM_TO = "LoRA转换从{}到{}" self.GENERATING_IMATRIX_FOR = "为{}生成IMatrix" self.MODEL_PATH_REQUIRED_FOR_IMATRIX = "IMatrix生成需要模型路径。" self.NO_ASSET_SELECTED_FOR_CUDA_CHECK = "未选择用于CUDA检查的资源" self.NO_QUANTIZATION_TYPE_SELECTED = "未选择量化类型。请至少选择一种量化类型。" self.STARTING_HF_TO_GGUF_CONVERSION = "开始HuggingFace到GGUF转换" self.MODEL_DIRECTORY_REQUIRED = "需要模型目录" self.HF_TO_GGUF_CONVERSION_COMMAND = "HF到GGUF转换命令:{}" self.CONVERTING_TO_GGUF = "将{}转换为GGUF" self.ERROR_STARTING_HF_TO_GGUF_CONVERSION = ( "启动HuggingFace到GGUF转换时出错:{}" ) self.HF_TO_GGUF_CONVERSION_TASK_STARTED = "HuggingFace到GGUF转换任务已开始" class _Spanish(_Localization): def __init__(self): super().__init__() # Interfaz de usuario general self.WINDOW_TITLE = "AutoGGUF (cuantificador automático de modelos GGUF)" self.RAM_USAGE = "Uso de RAM:" self.CPU_USAGE = "Uso de CPU:" self.BACKEND = "Backend de Llama.cpp:" self.REFRESH_BACKENDS = "Actualizar backends" self.MODELS_PATH = "Ruta de modelos:" self.OUTPUT_PATH = "Ruta de salida:" self.LOGS_PATH = "Ruta de registros:" self.BROWSE = "Explorar" self.AVAILABLE_MODELS = "Modelos disponibles:" self.REFRESH_MODELS = "Actualizar modelos" # Cuantificación self.QUANTIZATION_TYPE = "Tipo de cuantificación:" self.ALLOW_REQUANTIZE = "Permitir recuantificación" self.LEAVE_OUTPUT_TENSOR = "Dejar tensor de salida" self.PURE = "Puro" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "Incluir pesos:" self.EXCLUDE_WEIGHTS = "Excluir pesos:" self.USE_OUTPUT_TENSOR_TYPE = "Usar tipo de tensor de salida" self.USE_TOKEN_EMBEDDING_TYPE = "Usar tipo de embedding de token" self.KEEP_SPLIT = "Mantener división" self.KV_OVERRIDES = "Anulaciones KV:" self.ADD_NEW_OVERRIDE = "Añadir nueva anulación" self.QUANTIZE_MODEL = "Cuantificar modelo" self.EXTRA_ARGUMENTS = "Argumentos extra:" self.EXTRA_ARGUMENTS_LABEL = "Argumentos adicionales de línea de comandos" self.QUANTIZATION_COMMAND = "Comando de cuantificación" # Preajustes self.SAVE_PRESET = "Guardar preajuste" self.LOAD_PRESET = "Cargar preajuste" # Tareas self.TASKS = "Tareas:" # Descarga de llama.cpp self.DOWNLOAD_LLAMACPP = "Descargar llama.cpp" self.SELECT_RELEASE = "Seleccionar versión:" self.SELECT_ASSET = "Seleccionar asset:" self.EXTRACT_CUDA_FILES = "Extraer archivos CUDA" self.SELECT_CUDA_BACKEND = "Seleccionar backend CUDA:" self.DOWNLOAD = "Descargar" self.REFRESH_RELEASES = "Actualizar versiones" # Generación de IMatrix self.IMATRIX_GENERATION = "Generación de IMatrix" self.DATA_FILE = "Archivo de datos:" self.MODEL = "Modelo:" self.OUTPUT = "Salida:" self.OUTPUT_FREQUENCY = "Frecuencia de salida:" self.GPU_OFFLOAD = "Descarga en GPU:" self.AUTO = "Auto" self.GENERATE_IMATRIX = "Generar IMatrix" self.CONTEXT_SIZE = "Tamaño de contexto:" self.CONTEXT_SIZE_FOR_IMATRIX = "Tamaño de contexto para generación de IMatrix" self.THREADS = "Hilos:" self.NUMBER_OF_THREADS_FOR_IMATRIX = ( "Número de hilos para generación de IMatrix" ) self.IMATRIX_GENERATION_COMMAND = "Comando de generación de IMatrix" # Conversión LoRA self.LORA_CONVERSION = "Conversión LoRA" self.LORA_INPUT_PATH = "Ruta de entrada LoRA" self.LORA_OUTPUT_PATH = "Ruta de salida LoRA" self.SELECT_LORA_INPUT_DIRECTORY = "Seleccionar directorio de entrada LoRA" self.SELECT_LORA_OUTPUT_FILE = "Seleccionar archivo de salida LoRA" self.CONVERT_LORA = "Convertir LoRA" self.LORA_CONVERSION_COMMAND = "Comando de conversión LoRA" # Exportación LoRA self.EXPORT_LORA = "Exportar LoRA" self.GGML_LORA_ADAPTERS = "Adaptadores LoRA GGML" self.SELECT_LORA_ADAPTER_FILES = "Seleccionar archivos de adaptador LoRA" self.ADD_ADAPTER = "Añadir adaptador" self.DELETE_ADAPTER = "Eliminar" self.LORA_SCALE = "Escala LoRA" self.ENTER_LORA_SCALE_VALUE = "Introducir valor de escala LoRA (Opcional)" self.NUMBER_OF_THREADS_FOR_LORA_EXPORT = "Número de hilos para exportación LoRA" self.LORA_EXPORT_COMMAND = "Comando de exportación LoRA" # Conversión de HuggingFace a GGUF self.HF_TO_GGUF_CONVERSION = "Conversión de HuggingFace a GGUF" self.MODEL_DIRECTORY = "Directorio del modelo:" self.OUTPUT_FILE = "Archivo de salida:" self.OUTPUT_TYPE = "Tipo de salida:" self.VOCAB_ONLY = "Solo vocabulario" self.USE_TEMP_FILE = "Usar archivo temporal" self.NO_LAZY_EVALUATION = "Sin evaluación perezosa" self.MODEL_NAME = "Nombre del modelo:" self.VERBOSE = "Detallado" self.SPLIT_MAX_SIZE = "Tamaño máximo de división:" self.DRY_RUN = "Simulación" self.CONVERT_HF_TO_GGUF = "Convertir HF a GGUF" self.SELECT_HF_MODEL_DIRECTORY = "Seleccionar directorio del modelo HuggingFace" self.BROWSE_FOR_HF_MODEL_DIRECTORY = ( "Explorar directorio del modelo HuggingFace" ) self.BROWSE_FOR_HF_TO_GGUF_OUTPUT = ( "Explorar archivo de salida HuggingFace a GGUF" ) # Mensajes generales self.ERROR = "Error" self.WARNING = "Advertencia" self.PROPERTIES = "Propiedades" self.CANCEL = "Cancelar" self.RESTART = "Reiniciar" self.DELETE = "Eliminar" self.CONFIRM_DELETION = "¿Está seguro de que desea eliminar esta tarea?" self.TASK_RUNNING_WARNING = ( "Algunas tareas aún están en ejecución. ¿Está seguro de que desea salir?" ) self.YES = "Sí" self.NO = "No" self.COMPLETED = "Completado" # Tipos de archivo self.ALL_FILES = "Todos los archivos (*)" self.GGUF_FILES = "Archivos GGUF (*.gguf)" self.DAT_FILES = "Archivos DAT (*.dat)" self.JSON_FILES = "Archivos JSON (*.json)" self.BIN_FILES = "Archivos binarios (*.bin)" self.LORA_FILES = "Archivos LoRA (*.bin)" self.GGUF_AND_BIN_FILES = "Archivos GGUF y binarios (*.gguf *.bin)" self.SHARDED = "fragmentado" # Mensajes de estado self.DOWNLOAD_COMPLETE = "Descarga completa" self.CUDA_EXTRACTION_FAILED = "Falló la extracción de CUDA" self.PRESET_SAVED = "Preajuste guardado" self.PRESET_LOADED = "Preajuste cargado" self.NO_ASSET_SELECTED = "No se seleccionó ningún asset" self.DOWNLOAD_FAILED = "Falló la descarga" self.NO_BACKEND_SELECTED = "No se seleccionó ningún backend" self.NO_MODEL_SELECTED = "No se seleccionó ningún modelo" self.NO_SUITABLE_CUDA_BACKENDS = "No se encontraron backends CUDA adecuados" self.IN_PROGRESS = "En progreso" self.LLAMACPP_DOWNLOADED_EXTRACTED = ( "Binario de llama.cpp descargado y extraído en {0}" ) self.CUDA_FILES_EXTRACTED = "Archivos CUDA extraídos en" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "No se encontró un backend CUDA adecuado para la extracción" ) self.ERROR_FETCHING_RELEASES = "Error al obtener versiones: {0}" self.CONFIRM_DELETION_TITLE = "Confirmar eliminación" self.LOG_FOR = "Registro para {0}" self.FAILED_LOAD_PRESET = "Falló la carga del preajuste: {0}" self.INITIALIZING_AUTOGGUF = "Inicializando aplicación AutoGGUF" self.AUTOGGUF_INITIALIZATION_COMPLETE = "Inicialización de AutoGGUF completa" self.REFRESHING_BACKENDS = "Actualizando backends" self.NO_BACKENDS_AVAILABLE = "No hay backends disponibles" self.FOUND_VALID_BACKENDS = "Se encontraron {0} backends válidos" self.SAVING_PRESET = "Guardando preajuste" self.PRESET_SAVED_TO = "Preajuste guardado en {0}" self.LOADING_PRESET = "Cargando preajuste" self.PRESET_LOADED_FROM = "Preajuste cargado desde {0}" self.ADDING_KV_OVERRIDE = "Añadiendo anulación KV: {0}" self.SAVING_TASK_PRESET = "Guardando preajuste de tarea para {0}" self.TASK_PRESET_SAVED = "Preajuste de tarea guardado" self.TASK_PRESET_SAVED_TO = "Preajuste de tarea guardado en {0}" self.RESTARTING_TASK = "Reiniciando tarea: {0}" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "Descarga finalizada. Extraído en: {0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = ( "Binario de llama.cpp descargado y extraído en {0}" ) self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "No se encontró un backend CUDA adecuado para la extracción" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "Binario de llama.cpp descargado y extraído en {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "Actualizando versiones de llama.cpp" self.UPDATING_ASSET_LIST = "Actualizando lista de assets" self.UPDATING_CUDA_OPTIONS = "Actualizando opciones de CUDA" self.STARTING_LLAMACPP_DOWNLOAD = "Iniciando descarga de llama.cpp" self.UPDATING_CUDA_BACKENDS = "Actualizando backends CUDA" self.NO_CUDA_BACKEND_SELECTED = ( "No se seleccionó ningún backend CUDA para la extracción" ) self.EXTRACTING_CUDA_FILES = "Extrayendo archivos CUDA de {0} a {1}" self.DOWNLOAD_ERROR = "Error de descarga: {0}" self.SHOWING_TASK_CONTEXT_MENU = "Mostrando menú contextual de tarea" self.SHOWING_PROPERTIES_FOR_TASK = "Mostrando propiedades para la tarea: {0}" self.CANCELLING_TASK = "Cancelando tarea: {0}" self.CANCELED = "Cancelado" self.DELETING_TASK = "Eliminando tarea: {0}" self.LOADING_MODELS = "Cargando modelos" self.LOADED_MODELS = "Se cargaron {0} modelos" self.BROWSING_FOR_MODELS_DIRECTORY = "Explorando directorio de modelos" self.SELECT_MODELS_DIRECTORY = "Seleccionar directorio de modelos" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Explorando directorio de salida" self.SELECT_OUTPUT_DIRECTORY = "Seleccionar directorio de salida" self.BROWSING_FOR_LOGS_DIRECTORY = "Explorando directorio de registros" self.SELECT_LOGS_DIRECTORY = "Seleccionar directorio de registros" self.BROWSING_FOR_IMATRIX_FILE = "Explorando archivo IMatrix" self.SELECT_IMATRIX_FILE = "Seleccionar archivo IMatrix" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "Uso de CPU: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "Validando entradas de cuantificación" self.MODELS_PATH_REQUIRED = "Se requiere la ruta de modelos" self.OUTPUT_PATH_REQUIRED = "Se requiere la ruta de salida" self.LOGS_PATH_REQUIRED = "Se requiere la ruta de registros" self.STARTING_MODEL_QUANTIZATION = "Iniciando cuantificación del modelo" self.INPUT_FILE_NOT_EXIST = "El archivo de entrada '{0}' no existe." self.QUANTIZING_MODEL_TO = "Cuantificando {0} a {1}" self.QUANTIZATION_TASK_STARTED = "Tarea de cuantificación iniciada para {0}" self.ERROR_STARTING_QUANTIZATION = "Error al iniciar la cuantificación: {0}" self.UPDATING_MODEL_INFO = "Actualizando información del modelo: {0}" self.TASK_FINISHED = "Tarea finalizada: {0}" self.SHOWING_TASK_DETAILS_FOR = "Mostrando detalles de la tarea para: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "Explorando archivo de datos IMatrix" self.SELECT_DATA_FILE = "Seleccionar archivo de datos" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "Explorando archivo de modelo IMatrix" self.SELECT_MODEL_FILE = "Seleccionar archivo de modelo" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "Explorando archivo de salida IMatrix" self.SELECT_OUTPUT_FILE = "Seleccionar archivo de salida" self.STARTING_IMATRIX_GENERATION = "Iniciando generación de IMatrix" self.BACKEND_PATH_NOT_EXIST = "La ruta del backend no existe: {0}" self.GENERATING_IMATRIX = "Generando IMatrix" self.ERROR_STARTING_IMATRIX_GENERATION = ( "Error al iniciar la generación de IMatrix: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "Tarea de generación de IMatrix iniciada" self.ERROR_MESSAGE = "Error: {0}" self.TASK_ERROR = "Error de tarea: {0}" self.APPLICATION_CLOSING = "Cerrando aplicación" self.APPLICATION_CLOSED = "Aplicación cerrada" self.SELECT_QUANTIZATION_TYPE = "Seleccione el tipo de cuantificación" self.ALLOWS_REQUANTIZING = ( "Permite recuantificar tensores que ya han sido cuantificados" ) self.LEAVE_OUTPUT_WEIGHT = "Dejará output.weight sin (re)cuantificar" self.DISABLE_K_QUANT_MIXTURES = "Deshabilita las mezclas k-quant y cuantifica todos los tensores al mismo tipo" self.USE_DATA_AS_IMPORTANCE_MATRIX = "Usa los datos en el archivo como matriz de importancia para optimizaciones de cuantificación" self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Usa matriz de importancia para estos tensores" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "No usa matriz de importancia para estos tensores" ) self.OUTPUT_TENSOR_TYPE = "Tipo de tensor de salida:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Usa este tipo para el tensor output.weight" ) self.TOKEN_EMBEDDING_TYPE = "Tipo de embedding de token:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Usa este tipo para el tensor de embeddings de token" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "Generará el modelo cuantificado en los mismos fragmentos que la entrada" ) self.OVERRIDE_MODEL_METADATA = "Anular metadatos del modelo" self.INPUT_DATA_FILE_FOR_IMATRIX = ( "Archivo de datos de entrada para generación de IMatrix" ) self.MODEL_TO_BE_QUANTIZED = "Modelo a cuantificar" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = ( "Ruta de salida para el IMatrix generado" ) self.HOW_OFTEN_TO_SAVE_IMATRIX = "Con qué frecuencia guardar el IMatrix" self.SET_GPU_OFFLOAD_VALUE = "Establecer valor de descarga GPU (-ngl)" self.STARTING_LORA_CONVERSION = "Iniciando conversión LoRA" self.LORA_INPUT_PATH_REQUIRED = "Se requiere la ruta de entrada LoRA." self.LORA_OUTPUT_PATH_REQUIRED = "Se requiere la ruta de salida LoRA." self.ERROR_STARTING_LORA_CONVERSION = "Error al iniciar la conversión LoRA: {}" self.LORA_CONVERSION_TASK_STARTED = "Tarea de conversión LoRA iniciada." self.BROWSING_FOR_LORA_INPUT_DIRECTORY = ( "Explorando directorio de entrada LoRA..." ) self.BROWSING_FOR_LORA_OUTPUT_FILE = "Explorando archivo de salida LoRA..." self.CONVERTING_LORA = "Conversión LoRA" self.LORA_CONVERSION_FINISHED = "Conversión LoRA finalizada." self.LORA_FILE_MOVED = "Archivo LoRA movido de {} a {}." self.LORA_FILE_NOT_FOUND = "Archivo LoRA no encontrado: {}." self.ERROR_MOVING_LORA_FILE = "Error al mover el archivo LoRA: {}" self.MODEL_PATH_REQUIRED = "Se requiere la ruta del modelo." self.AT_LEAST_ONE_LORA_ADAPTER_REQUIRED = ( "Se requiere al menos un adaptador LoRA." ) self.INVALID_LORA_SCALE_VALUE = "Valor de escala LoRA inválido." self.ERROR_STARTING_LORA_EXPORT = "Error al iniciar la exportación LoRA: {}" self.LORA_EXPORT_TASK_STARTED = "Tarea de exportación LoRA iniciada." self.EXPORTING_LORA = "Exportando LoRA..." self.BROWSING_FOR_EXPORT_LORA_MODEL_FILE = ( "Explorando archivo de modelo para exportación LoRA..." ) self.BROWSING_FOR_EXPORT_LORA_OUTPUT_FILE = ( "Explorando archivo de salida para exportación LoRA..." ) self.ADDING_LORA_ADAPTER = "Añadiendo adaptador LoRA..." self.DELETING_LORA_ADAPTER = "Eliminando adaptador LoRA..." self.SELECT_LORA_ADAPTER_FILE = "Seleccionar archivo de adaptador LoRA" self.STARTING_LORA_EXPORT = "Iniciando exportación LoRA..." self.SELECT_OUTPUT_TYPE = "Seleccionar tipo de salida (GGUF o GGML)" self.BASE_MODEL = "Modelo base" self.SELECT_BASE_MODEL_FILE = "Seleccionar archivo de modelo base (GGUF)" self.BASE_MODEL_PATH_REQUIRED = ( "Se requiere la ruta del modelo base para la salida GGUF." ) self.BROWSING_FOR_BASE_MODEL_FILE = "Explorando archivo de modelo base..." self.SELECT_BASE_MODEL_FOLDER = ( "Seleccionar carpeta de modelo base (que contiene safetensors)" ) self.BROWSING_FOR_BASE_MODEL_FOLDER = "Explorando carpeta de modelo base..." self.LORA_CONVERSION_FROM_TO = "Conversión LoRA de {} a {}" self.GENERATING_IMATRIX_FOR = "Generando IMatrix para {}" self.MODEL_PATH_REQUIRED_FOR_IMATRIX = ( "Se requiere la ruta del modelo para la generación de IMatrix." ) self.NO_ASSET_SELECTED_FOR_CUDA_CHECK = ( "No se seleccionó ningún asset para la verificación CUDA" ) self.NO_QUANTIZATION_TYPE_SELECTED = "No se seleccionó ningún tipo de cuantificación. Por favor, seleccione al menos un tipo de cuantificación." self.STARTING_HF_TO_GGUF_CONVERSION = ( "Iniciando conversión de HuggingFace a GGUF" ) self.MODEL_DIRECTORY_REQUIRED = "Se requiere el directorio del modelo" self.HF_TO_GGUF_CONVERSION_COMMAND = "Comando de conversión de HF a GGUF: {}" self.CONVERTING_TO_GGUF = "Convirtiendo {} a GGUF" self.ERROR_STARTING_HF_TO_GGUF_CONVERSION = ( "Error al iniciar la conversión de HuggingFace a GGUF: {}" ) self.HF_TO_GGUF_CONVERSION_TASK_STARTED = ( "Tarea de conversión de HuggingFace a GGUF iniciada" ) class _Hindi(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (स्वचालित GGUF मॉडल क्वांटाइज़र)" self.RAM_USAGE = "RAM उपयोग:" self.CPU_USAGE = "CPU उपयोग:" self.BACKEND = "Llama.cpp बैकएंड:" self.REFRESH_BACKENDS = "बैकएंड रीफ्रेश करें" self.MODELS_PATH = "मॉडल पथ:" self.OUTPUT_PATH = "आउटपुट पथ:" self.LOGS_PATH = "लॉग पथ:" self.BROWSE = "ब्राउज़ करें" self.AVAILABLE_MODELS = "उपलब्ध मॉडल:" self.QUANTIZATION_TYPE = "क्वांटाइजेशन प्रकार:" self.ALLOW_REQUANTIZE = "पुनः क्वांटाइज़ करने की अनुमति दें" self.LEAVE_OUTPUT_TENSOR = "आउटपुट टेंसर छोड़ें" self.PURE = "शुद्ध" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "वेट शामिल करें:" self.EXCLUDE_WEIGHTS = "वेट बाहर रखें:" self.USE_OUTPUT_TENSOR_TYPE = "आउटपुट टेंसर प्रकार का उपयोग करें" self.USE_TOKEN_EMBEDDING_TYPE = "टोकन एम्बेडिंग प्रकार का उपयोग करें" self.KEEP_SPLIT = "विभाजन रखें" self.KV_OVERRIDES = "KV ओवरराइड:" self.ADD_NEW_OVERRIDE = "नया ओवरराइड जोड़ें" self.QUANTIZE_MODEL = "मॉडल क्वांटाइज़ करें" self.SAVE_PRESET = "प्रीसेट सहेजें" self.LOAD_PRESET = "प्रीसेट लोड करें" self.TASKS = "कार्य:" self.DOWNLOAD_LLAMACPP = "llama.cpp डाउनलोड करें" self.SELECT_RELEASE = "रिलीज़ चुनें:" self.SELECT_ASSET = "एसेट चुनें:" self.EXTRACT_CUDA_FILES = "CUDA फ़ाइलें निकालें" self.SELECT_CUDA_BACKEND = "CUDA बैकएंड चुनें:" self.DOWNLOAD = "डाउनलोड करें" self.IMATRIX_GENERATION = "IMatrix उत्पादन" self.DATA_FILE = "डेटा फ़ाइल:" self.MODEL = "मॉडल:" self.OUTPUT = "आउटपुट:" self.OUTPUT_FREQUENCY = "आउटपुट आवृत्ति:" self.GPU_OFFLOAD = "GPU ऑफलोड:" self.AUTO = "स्वचालित" self.GENERATE_IMATRIX = "IMatrix उत्पन्न करें" self.ERROR = "त्रुटि" self.WARNING = "चेतावनी" self.PROPERTIES = "गुण" self.WINDOW_TITLE = "AutoGGUF (स्वचालित GGUF मॉडल क्वांटाइज़र)" self.RAM_USAGE = "RAM उपयोग:" self.CPU_USAGE = "CPU उपयोग:" self.BACKEND = "Llama.cpp बैकएंड:" self.REFRESH_BACKENDS = "बैकएंड रीफ्रेश करें" self.MODELS_PATH = "मॉडल पथ:" self.OUTPUT_PATH = "आउटपुट पथ:" self.LOGS_PATH = "लॉग पथ:" self.BROWSE = "ब्राउज़ करें" self.AVAILABLE_MODELS = "उपलब्ध मॉडल:" self.QUANTIZATION_TYPE = "क्वांटाइजेशन प्रकार:" self.ALLOW_REQUANTIZE = "पुनः क्वांटाइज़ करने की अनुमति दें" self.LEAVE_OUTPUT_TENSOR = "आउटपुट टेंसर छोड़ें" self.PURE = "शुद्ध" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "वेट शामिल करें:" self.EXCLUDE_WEIGHTS = "वेट बाहर रखें:" self.USE_OUTPUT_TENSOR_TYPE = "आउटपुट टेंसर प्रकार का उपयोग करें" self.USE_TOKEN_EMBEDDING_TYPE = "टोकन एम्बेडिंग प्रकार का उपयोग करें" self.KEEP_SPLIT = "विभाजन रखें" self.KV_OVERRIDES = "KV ओवरराइड:" self.ADD_NEW_OVERRIDE = "नया ओवरराइड जोड़ें" self.QUANTIZE_MODEL = "मॉडल क्वांटाइज़ करें" self.SAVE_PRESET = "प्रीसेट सहेजें" self.LOAD_PRESET = "प्रीसेट लोड करें" self.TASKS = "कार्य:" self.DOWNLOAD_LLAMACPP = "llama.cpp डाउनलोड करें" self.SELECT_RELEASE = "रिलीज़ चुनें:" self.SELECT_ASSET = "एसेट चुनें:" self.EXTRACT_CUDA_FILES = "CUDA फ़ाइलें निकालें" self.SELECT_CUDA_BACKEND = "CUDA बैकएंड चुनें:" self.DOWNLOAD = "डाउनलोड करें" self.IMATRIX_GENERATION = "IMatrix उत्पादन" self.DATA_FILE = "डेटा फ़ाइल:" self.MODEL = "मॉडल:" self.OUTPUT = "आउटपुट:" self.OUTPUT_FREQUENCY = "आउटपुट आवृत्ति:" self.GPU_OFFLOAD = "GPU ऑफलोड:" self.AUTO = "स्वचालित" self.GENERATE_IMATRIX = "IMatrix उत्पन्न करें" self.ERROR = "त्रुटि" self.WARNING = "चेतावनी" self.PROPERTIES = "गुण" self.CANCEL = "रद्द करें" self.RESTART = "पुनः आरंभ करें" self.DELETE = "हटाएं" self.CONFIRM_DELETION = "क्या आप वाकई इस कार्य को हटाना चाहते हैं?" self.TASK_RUNNING_WARNING = ( "कुछ कार्य अभी भी चल रहे हैं। क्या आप वाकई बाहर निकलना चाहते हैं?" ) self.YES = "हां" self.NO = "नहीं" self.DOWNLOAD_COMPLETE = "डाउनलोड पूरा हुआ" self.CUDA_EXTRACTION_FAILED = "CUDA निष्कर्षण विफल" self.PRESET_SAVED = "प्रीसेट सहेजा गया" self.PRESET_LOADED = "प्रीसेट लोड किया गया" self.NO_ASSET_SELECTED = "कोई एसेट चयनित नहीं" self.DOWNLOAD_FAILED = "डाउनलोड विफल" self.NO_BACKEND_SELECTED = "कोई बैकएंड चयनित नहीं" self.NO_MODEL_SELECTED = "कोई मॉडल चयनित नहीं" self.REFRESH_RELEASES = "रिलीज़ रीफ्रेश करें" self.NO_SUITABLE_CUDA_BACKENDS = "कोई उपयुक्त CUDA बैकएंड नहीं मिला" self.LLAMACPP_DOWNLOADED_EXTRACTED = ( "llama.cpp बाइनरी डाउनलोड और {0} में निकाली गई\nCUDA फ़ाइलें {1} में निकाली गईं" ) self.CUDA_FILES_EXTRACTED = "CUDA फ़ाइलें निकाली गईं" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "निष्कर्षण के लिए कोई उपयुक्त CUDA बैकएंड नहीं मिला" ) self.ERROR_FETCHING_RELEASES = "रिलीज़ प्राप्त करने में त्रुटि: {0}" self.CONFIRM_DELETION_TITLE = "हटाने की पुष्टि करें" self.LOG_FOR = "{0} के लिए लॉग" self.ALL_FILES = "सभी फ़ाइलें (*)" self.GGUF_FILES = "GGUF फ़ाइलें (*.gguf)" self.DAT_FILES = "DAT फ़ाइलें (*.dat)" self.JSON_FILES = "JSON फ़ाइलें (*.json)" self.FAILED_LOAD_PRESET = "प्रीसेट लोड करने में विफल: {0}" self.INITIALIZING_AUTOGGUF = "AutoGGUF एप्लिकेशन प्रारंभ हो रहा है" self.AUTOGGUF_INITIALIZATION_COMPLETE = "AutoGGUF प्रारंभीकरण पूरा हुआ" self.REFRESHING_BACKENDS = "बैकएंड रीफ्रेश हो रहे हैं" self.NO_BACKENDS_AVAILABLE = "कोई बैकएंड उपलब्ध नहीं" self.FOUND_VALID_BACKENDS = "{0} मान्य बैकएंड मिले" self.SAVING_PRESET = "प्रीसेट सहेजा जा रहा है" self.PRESET_SAVED_TO = "प्रीसेट {0} में सहेजा गया" self.LOADING_PRESET = "प्रीसेट लोड हो रहा है" self.PRESET_LOADED_FROM = "{0} से प्रीसेट लोड किया गया" self.ADDING_KV_OVERRIDE = "KV ओवरराइड जोड़ा जा रहा है: {0}" self.SAVING_TASK_PRESET = "{0} के लिए कार्य प्रीसेट सहेजा जा रहा है" self.TASK_PRESET_SAVED = "कार्य प्रीसेट सहेजा गया" self.TASK_PRESET_SAVED_TO = "कार्य प्रीसेट {0} में सहेजा गया" self.RESTARTING_TASK = "कार्य पुनः आरंभ हो रहा है: {0}" self.IN_PROGRESS = "प्रगति में" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "डाउनलोड समाप्त। निकाला गया: {0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = ( "llama.cpp बाइनरी डाउनलोड और {0} में निकाली गई\nCUDA फ़ाइलें {1} में निकाली गईं" ) self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "निष्कर्षण के लिए कोई उपयुक्त CUDA बैकएंड नहीं मिला" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "llama.cpp बाइनरी डाउनलोड और {0} में निकाली गई" ) self.REFRESHING_LLAMACPP_RELEASES = "llama.cpp रिलीज़ रीफ्रेश हो रही हैं" self.UPDATING_ASSET_LIST = "एसेट सूची अपडेट हो रही है" self.UPDATING_CUDA_OPTIONS = "CUDA विकल्प अपडेट हो रहे हैं" self.STARTING_LLAMACPP_DOWNLOAD = "llama.cpp डाउनलोड शुरू हो रहा है" self.UPDATING_CUDA_BACKENDS = "CUDA बैकएंड अपडेट हो रहे हैं" self.NO_CUDA_BACKEND_SELECTED = "निष्कर्षण के लिए कोई CUDA बैकएंड चयनित नहीं" self.EXTRACTING_CUDA_FILES = "{0} से {1} में CUDA फ़ाइलें निकाली जा रही हैं" self.DOWNLOAD_ERROR = "डाउनलोड त्रुटि: {0}" self.SHOWING_TASK_CONTEXT_MENU = "कार्य संदर्भ मेनू दिखाया जा रहा है" self.SHOWING_PROPERTIES_FOR_TASK = "कार्य के लिए गुण दिखाए जा रहे हैं: {0}" self.CANCELLING_TASK = "कार्य रद्द किया जा रहा है: {0}" self.CANCELED = "रद्द किया गया" self.DELETING_TASK = "कार्य हटाया जा रहा है: {0}" self.LOADING_MODELS = "मॉडल लोड हो रहे हैं" self.LOADED_MODELS = "{0} मॉडल लोड किए गए" self.BROWSING_FOR_MODELS_DIRECTORY = "मॉडल निर्देशिका के लिए ब्राउज़ किया जा रहा है" self.SELECT_MODELS_DIRECTORY = "मॉडल निर्देशिका चुनें" self.BROWSING_FOR_OUTPUT_DIRECTORY = "आउटपुट निर्देशिका के लिए ब्राउज़ किया जा रहा है" self.SELECT_OUTPUT_DIRECTORY = "आउटपुट निर्देशिका चुनें" self.BROWSING_FOR_LOGS_DIRECTORY = "लॉग निर्देशिका के लिए ब्राउज़ किया जा रहा है" self.SELECT_LOGS_DIRECTORY = "लॉग निर्देशिका चुनें" self.BROWSING_FOR_IMATRIX_FILE = "IMatrix फ़ाइल के लिए ब्राउज़ किया जा रहा है" self.SELECT_IMATRIX_FILE = "IMatrix फ़ाइल चुनें" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "CPU उपयोग: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "क्वांटाइजेशन इनपुट सत्यापित किए जा रहे हैं" self.MODELS_PATH_REQUIRED = "मॉडल पथ आवश्यक है" self.OUTPUT_PATH_REQUIRED = "आउटपुट पथ आवश्यक है" self.LOGS_PATH_REQUIRED = "लॉग पथ आवश्यक है" self.STARTING_MODEL_QUANTIZATION = "मॉडल क्वांटाइजेशन शुरू हो रहा है" self.INPUT_FILE_NOT_EXIST = "इनपुट फ़ाइल '{0}' मौजूद नहीं है।" self.QUANTIZING_MODEL_TO = "{0} को {1} में क्वांटाइज़ किया जा रहा है" self.QUANTIZATION_TASK_STARTED = "{0} के लिए क्वांटाइजेशन कार्य शुरू हुआ" self.ERROR_STARTING_QUANTIZATION = "क्वांटाइजेशन शुरू करने में त्रुटि: {0}" self.UPDATING_MODEL_INFO = "मॉडल जानकारी अपडेट हो रही है: {0}" self.TASK_FINISHED = "कार्य समाप्त: {0}" self.SHOWING_TASK_DETAILS_FOR = "कार्य विवरण दिखाए जा रहे हैं: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = ( "IMatrix डेटा फ़ाइल के लिए ब्राउज़ किया जा रहा है" ) self.SELECT_DATA_FILE = "डेटा फ़ाइल चुनें" self.BROWSING_FOR_IMATRIX_MODEL_FILE = ( "IMatrix मॉडल फ़ाइल के लिए ब्राउज़ किया जा रहा है" ) self.SELECT_MODEL_FILE = "मॉडल फ़ाइल चुनें" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = ( "IMatrix आउटपुट फ़ाइल के लिए ब्राउज़ किया जा रहा है" ) self.SELECT_OUTPUT_FILE = "आउटपुट फ़ाइल चुनें" self.STARTING_IMATRIX_GENERATION = "IMatrix उत्पादन शुरू हो रहा है" self.BACKEND_PATH_NOT_EXIST = "बैकएंड पथ मौजूद नहीं है: {0}" self.GENERATING_IMATRIX = "IMatrix उत्पन्न किया जा रहा है" self.ERROR_STARTING_IMATRIX_GENERATION = "IMatrix उत्पादन शुरू करने में त्रुटि: {0}" self.IMATRIX_GENERATION_TASK_STARTED = "IMatrix उत्पादन कार्य शुरू हुआ" self.ERROR_MESSAGE = "त्रुटि: {0}" self.TASK_ERROR = "कार्य त्रुटि: {0}" self.APPLICATION_CLOSING = "एप्लिकेशन बंद हो रहा है" self.APPLICATION_CLOSED = "एप्लिकेशन बंद हो गया" self.SELECT_QUANTIZATION_TYPE = "क्वांटाइजेशन प्रकार चुनें" self.ALLOWS_REQUANTIZING = ( "पहले से क्वांटाइज़ किए गए टेंसर को पुनः क्वांटाइज़ करने की अनुमति देता है" ) self.LEAVE_OUTPUT_WEIGHT = "output.weight को अक्वांटाइज़ (या पुनः क्वांटाइज़) छोड़ देगा" self.DISABLE_K_QUANT_MIXTURES = ( "k-quant मिश्रण को अक्षम करें और सभी टेंसर को एक ही प्रकार में क्वांटाइज़ करें" ) self.USE_DATA_AS_IMPORTANCE_MATRIX = ( "क्वांट अनुकूलन के लिए फ़ाइल में डेटा को महत्व मैट्रिक्स के रूप में उपयोग करें" ) self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = "इन टेंसर के लिए महत्व मैट्रिक्स का उपयोग करें" self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "इन टेंसर के लिए महत्व मैट्रिक्स का उपयोग न करें" ) self.OUTPUT_TENSOR_TYPE = "आउटपुट टेंसर प्रकार:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "output.weight टेंसर के लिए इस प्रकार का उपयोग करें" ) self.TOKEN_EMBEDDING_TYPE = "टोकन एम्बेडिंग प्रकार:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "टोकन एम्बेडिंग टेंसर के लिए इस प्रकार का उपयोग करें" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "इनपुट के समान शार्ड्स में क्वांटाइज़ किए गए मॉडल को उत्पन्न करेगा" ) self.OVERRIDE_MODEL_METADATA = "मॉडल मेटाडेटा को ओवरराइड करें" self.INPUT_DATA_FILE_FOR_IMATRIX = "IMatrix उत्पादन के लिए इनपुट डेटा फ़ाइल" self.MODEL_TO_BE_QUANTIZED = "क्वांटाइज़ किए जाने वाला मॉडल" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = "उत्पन्न IMatrix के लिए आउटपुट पथ" self.HOW_OFTEN_TO_SAVE_IMATRIX = "IMatrix को कितनी बार सहेजना है" self.SET_GPU_OFFLOAD_VALUE = "GPU ऑफलोड मान सेट करें (-ngl)" self.COMPLETED = "पूरा हुआ" self.REFRESH_MODELS = "मॉडल रीफ्रेश करें" class _Russian(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (автоматический квантователь моделей GGUF)" self.RAM_USAGE = "Использование ОЗУ:" self.CPU_USAGE = "Использование ЦП:" self.BACKEND = "Бэкенд Llama.cpp:" self.REFRESH_BACKENDS = "Обновить бэкенды" self.MODELS_PATH = "Путь к моделям:" self.OUTPUT_PATH = "Путь вывода:" self.LOGS_PATH = "Путь к логам:" self.BROWSE = "Обзор" self.AVAILABLE_MODELS = "Доступные модели:" self.QUANTIZATION_TYPE = "Тип квантования:" self.ALLOW_REQUANTIZE = "Разрешить переквантование" self.LEAVE_OUTPUT_TENSOR = "Оставить выходной тензор" self.PURE = "Чистый" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "Включить веса:" self.EXCLUDE_WEIGHTS = "Исключить веса:" self.USE_OUTPUT_TENSOR_TYPE = "Использовать тип выходного тензора" self.USE_TOKEN_EMBEDDING_TYPE = "Использовать тип встраивания токенов" self.KEEP_SPLIT = "Сохранить разделение" self.KV_OVERRIDES = "KV переопределения:" self.ADD_NEW_OVERRIDE = "Добавить новое переопределение" self.QUANTIZE_MODEL = "Квантовать модель" self.SAVE_PRESET = "Сохранить пресет" self.LOAD_PRESET = "Загрузить пресет" self.TASKS = "Задачи:" self.DOWNLOAD_LLAMACPP = "Скачать llama.cpp" self.SELECT_RELEASE = "Выбрать релиз:" self.SELECT_ASSET = "Выбрать актив:" self.EXTRACT_CUDA_FILES = "Извлечь файлы CUDA" self.SELECT_CUDA_BACKEND = "Выбрать бэкенд CUDA:" self.DOWNLOAD = "Скачать" self.IMATRIX_GENERATION = "Генерация IMatrix" self.DATA_FILE = "Файл данных:" self.MODEL = "Модель:" self.OUTPUT = "Вывод:" self.OUTPUT_FREQUENCY = "Частота вывода:" self.GPU_OFFLOAD = "Разгрузка GPU:" self.AUTO = "Авто" self.GENERATE_IMATRIX = "Сгенерировать IMatrix" self.ERROR = "Ошибка" self.WARNING = "Предупреждение" self.PROPERTIES = "Свойства" self.CANCEL = "Отмена" self.RESTART = "Перезапуск" self.DELETE = "Удалить" self.CONFIRM_DELETION = "Вы уверены, что хотите удалить эту задачу?" self.TASK_RUNNING_WARNING = ( "Некоторые задачи все еще выполняются. Вы уверены, что хотите выйти?" ) self.YES = "Да" self.NO = "Нет" self.DOWNLOAD_COMPLETE = "Загрузка завершена" self.CUDA_EXTRACTION_FAILED = "Извлечение CUDA не удалось" self.PRESET_SAVED = "Пресет сохранен" self.PRESET_LOADED = "Пресет загружен" self.NO_ASSET_SELECTED = "Актив не выбран" self.DOWNLOAD_FAILED = "Загрузка не удалась" self.NO_BACKEND_SELECTED = "Бэкенд не выбран" self.NO_MODEL_SELECTED = "Модель не выбрана" self.REFRESH_RELEASES = "Обновить релизы" self.NO_SUITABLE_CUDA_BACKENDS = "Подходящие бэкенды CUDA не найдены" self.LLAMACPP_DOWNLOADED_EXTRACTED = "Бинарный файл llama.cpp загружен и извлечен в {0}\nФайлы CUDA извлечены в {1}" self.CUDA_FILES_EXTRACTED = "Файлы CUDA извлечены в" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "Подходящий бэкенд CUDA для извлечения не найден" ) self.ERROR_FETCHING_RELEASES = "Ошибка получения релизов: {0}" self.CONFIRM_DELETION_TITLE = "Подтвердить удаление" self.LOG_FOR = "Лог для {0}" self.ALL_FILES = "Все файлы (*)" self.GGUF_FILES = "Файлы GGUF (*.gguf)" self.DAT_FILES = "Файлы DAT (*.dat)" self.JSON_FILES = "Файлы JSON (*.json)" self.FAILED_LOAD_PRESET = "Не удалось загрузить пресет: {0}" self.INITIALIZING_AUTOGGUF = "Инициализация приложения AutoGGUF" self.AUTOGGUF_INITIALIZATION_COMPLETE = "Инициализация AutoGGUF завершена" self.REFRESHING_BACKENDS = "Обновление бэкендов" self.NO_BACKENDS_AVAILABLE = "Бэкенды недоступны" self.FOUND_VALID_BACKENDS = "Найдено {0} действительных бэкендов" self.SAVING_PRESET = "Сохранение пресета" self.PRESET_SAVED_TO = "Пресет сохранен в {0}" self.LOADING_PRESET = "Загрузка пресета" self.PRESET_LOADED_FROM = "Пресет загружен из {0}" self.ADDING_KV_OVERRIDE = "Добавление KV переопределения: {0}" self.SAVING_TASK_PRESET = "Сохранение пресета задачи для {0}" self.TASK_PRESET_SAVED = "Пресет задачи сохранен" self.TASK_PRESET_SAVED_TO = "Пресет задачи сохранен в {0}" self.RESTARTING_TASK = "Перезапуск задачи: {0}" self.IN_PROGRESS = "В процессе" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "Загрузка завершена. Извлечено в: {0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "Бинарный файл llama.cpp загружен и извлечен в {0}\nФайлы CUDA извлечены в {1}" self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "Подходящий бэкенд CUDA для извлечения не найден" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "Бинарный файл llama.cpp загружен и извлечен в {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "Обновление релизов llama.cpp" self.UPDATING_ASSET_LIST = "Обновление списка активов" self.UPDATING_CUDA_OPTIONS = "Обновление параметров CUDA" self.STARTING_LLAMACPP_DOWNLOAD = "Начало загрузки llama.cpp" self.UPDATING_CUDA_BACKENDS = "Обновление бэкендов CUDA" self.NO_CUDA_BACKEND_SELECTED = "Бэкенд CUDA для извлечения не выбран" self.EXTRACTING_CUDA_FILES = "Извлечение файлов CUDA из {0} в {1}" self.DOWNLOAD_ERROR = "Ошибка загрузки: {0}" self.SHOWING_TASK_CONTEXT_MENU = "Отображение контекстного меню задачи" self.SHOWING_PROPERTIES_FOR_TASK = "Отображение свойств задачи: {0}" self.CANCELLING_TASK = "Отмена задачи: {0}" self.CANCELED = "Отменено" self.DELETING_TASK = "Удаление задачи: {0}" self.LOADING_MODELS = "Загрузка моделей" self.LOADED_MODELS = "Загружено {0} моделей" self.BROWSING_FOR_MODELS_DIRECTORY = "Поиск каталога моделей" self.SELECT_MODELS_DIRECTORY = "Выберите каталог моделей" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Поиск выходного каталога" self.SELECT_OUTPUT_DIRECTORY = "Выберите выходной каталог" self.BROWSING_FOR_LOGS_DIRECTORY = "Поиск каталога логов" self.SELECT_LOGS_DIRECTORY = "Выберите каталог логов" self.BROWSING_FOR_IMATRIX_FILE = "Поиск файла IMatrix" self.SELECT_IMATRIX_FILE = "Выберите файл IMatrix" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} МБ / {2} МБ)" self.CPU_USAGE_FORMAT = "Использование ЦП: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "Проверка входных данных квантования" self.MODELS_PATH_REQUIRED = "Требуется путь к моделям" self.OUTPUT_PATH_REQUIRED = "Требуется путь вывода" self.LOGS_PATH_REQUIRED = "Требуется путь к логам" self.STARTING_MODEL_QUANTIZATION = "Начало квантования модели" self.INPUT_FILE_NOT_EXIST = "Входной файл '{0}' не существует." self.QUANTIZING_MODEL_TO = "Квантование {0} в {1}" self.QUANTIZATION_TASK_STARTED = "Задача квантования запущена для {0}" self.ERROR_STARTING_QUANTIZATION = "Ошибка запуска квантования: {0}" self.UPDATING_MODEL_INFO = "Обновление информации о модели: {0}" self.TASK_FINISHED = "Задача завершена: {0}" self.SHOWING_TASK_DETAILS_FOR = "Отображение сведений о задаче для: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "Поиск файла данных IMatrix" self.SELECT_DATA_FILE = "Выберите файл данных" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "Поиск файла модели IMatrix" self.SELECT_MODEL_FILE = "Выберите файл модели" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "Поиск выходного файла IMatrix" self.SELECT_OUTPUT_FILE = "Выберите выходной файл" self.STARTING_IMATRIX_GENERATION = "Начало генерации IMatrix" self.BACKEND_PATH_NOT_EXIST = "Путь бэкенда не существует: {0}" self.GENERATING_IMATRIX = "Генерация IMatrix" self.ERROR_STARTING_IMATRIX_GENERATION = "Ошибка запуска генерации IMatrix: {0}" self.IMATRIX_GENERATION_TASK_STARTED = "Задача генерации IMatrix запущена" self.ERROR_MESSAGE = "Ошибка: {0}" self.TASK_ERROR = "Ошибка задачи: {0}" self.APPLICATION_CLOSING = "Закрытие приложения" self.APPLICATION_CLOSED = "Приложение закрыто" self.SELECT_QUANTIZATION_TYPE = "Выберите тип квантования" self.ALLOWS_REQUANTIZING = ( "Позволяет переквантовать тензоры, которые уже были квантованы" ) self.LEAVE_OUTPUT_WEIGHT = "Оставит output.weight не (пере)квантованным" self.DISABLE_K_QUANT_MIXTURES = ( "Отключить k-квантовые смеси и квантовать все тензоры к одному типу" ) self.USE_DATA_AS_IMPORTANCE_MATRIX = "Использовать данные в файле как матрицу важности для оптимизации квантования" self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Использовать матрицу важности для этих тензоров" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Не использовать матрицу важности для этих тензоров" ) self.OUTPUT_TENSOR_TYPE = "Тип выходного тензора:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Использовать этот тип для тензора output.weight" ) self.TOKEN_EMBEDDING_TYPE = "Тип встраивания токенов:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Использовать этот тип для тензора встраивания токенов" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = "Будет генерировать квантованную модель в тех же шардах, что и входные данные" self.OVERRIDE_MODEL_METADATA = "Переопределить метаданные модели" self.INPUT_DATA_FILE_FOR_IMATRIX = "Входной файл данных для генерации IMatrix" self.MODEL_TO_BE_QUANTIZED = "Модель для квантования" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = ( "Выходной путь для сгенерированного IMatrix" ) self.HOW_OFTEN_TO_SAVE_IMATRIX = "Как часто сохранять IMatrix" self.SET_GPU_OFFLOAD_VALUE = "Установить значение разгрузки GPU (-ngl)" self.COMPLETED = "Завершено" self.REFRESH_MODELS = "Обновить модели" class _Ukrainian(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (автоматичний квантувальник моделей GGUF)" self.RAM_USAGE = "Використання ОЗУ:" self.CPU_USAGE = "Використання ЦП:" self.BACKEND = "Бекенд Llama.cpp:" self.REFRESH_BACKENDS = "Оновити бекенди" self.MODELS_PATH = "Шлях до моделей:" self.OUTPUT_PATH = "Шлях виводу:" self.LOGS_PATH = "Шлях до логів:" self.BROWSE = "Огляд" self.AVAILABLE_MODELS = "Доступні моделі:" self.QUANTIZATION_TYPE = "Тип квантування:" self.ALLOW_REQUANTIZE = "Дозволити переквантування" self.LEAVE_OUTPUT_TENSOR = "Залишити вихідний тензор" self.PURE = "Чистий" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "Включити ваги:" self.EXCLUDE_WEIGHTS = "Виключити ваги:" self.USE_OUTPUT_TENSOR_TYPE = "Використовувати тип вихідного тензора" self.USE_TOKEN_EMBEDDING_TYPE = "Використовувати тип вбудовування токенів" self.KEEP_SPLIT = "Зберегти розділення" self.KV_OVERRIDES = "KV перевизначення:" self.ADD_NEW_OVERRIDE = "Додати нове перевизначення" self.QUANTIZE_MODEL = "Квантувати модель" self.SAVE_PRESET = "Зберегти пресет" self.LOAD_PRESET = "Завантажити пресет" self.TASKS = "Завдання:" self.DOWNLOAD_LLAMACPP = "Завантажити llama.cpp" self.SELECT_RELEASE = "Вибрати реліз:" self.SELECT_ASSET = "Вибрати актив:" self.EXTRACT_CUDA_FILES = "Витягнути файли CUDA" self.SELECT_CUDA_BACKEND = "Вибрати бекенд CUDA:" self.DOWNLOAD = "Завантажити" self.IMATRIX_GENERATION = "Генерація IMatrix" self.DATA_FILE = "Файл даних:" self.MODEL = "Модель:" self.OUTPUT = "Вивід:" self.OUTPUT_FREQUENCY = "Частота виводу:" self.GPU_OFFLOAD = "Розвантаження GPU:" self.AUTO = "Авто" self.GENERATE_IMATRIX = "Згенерувати IMatrix" self.ERROR = "Помилка" self.WARNING = "Попередження" self.PROPERTIES = "Властивості" self.CANCEL = "Скасувати" self.RESTART = "Перезапустити" self.DELETE = "Видалити" self.CONFIRM_DELETION = "Ви впевнені, що хочете видалити це завдання?" self.TASK_RUNNING_WARNING = ( "Деякі завдання все ще виконуються. Ви впевнені, що хочете вийти?" ) self.YES = "Так" self.NO = "Ні" self.DOWNLOAD_COMPLETE = "Завантаження завершено" self.CUDA_EXTRACTION_FAILED = "Витягнення CUDA не вдалося" self.PRESET_SAVED = "Пресет збережено" self.PRESET_LOADED = "Пресет завантажено" self.NO_ASSET_SELECTED = "Актив не вибрано" self.DOWNLOAD_FAILED = "Завантаження не вдалося" self.NO_BACKEND_SELECTED = "Бекенд не вибрано" self.NO_MODEL_SELECTED = "Модель не вибрано" self.REFRESH_RELEASES = "Оновити релізи" self.NO_SUITABLE_CUDA_BACKENDS = "Підходящі бекенди CUDA не знайдено" self.LLAMACPP_DOWNLOADED_EXTRACTED = "Бінарний файл llama.cpp завантажено та витягнуто в {0}\nФайли CUDA витягнуто в {1}" self.CUDA_FILES_EXTRACTED = "Файли CUDA витягнуто в" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "Підходящий бекенд CUDA для витягнення не знайдено" ) self.ERROR_FETCHING_RELEASES = "Помилка отримання релізів: {0}" self.CONFIRM_DELETION_TITLE = "Підтвердити видалення" self.LOG_FOR = "Лог для {0}" self.ALL_FILES = "Всі файли (*)" self.GGUF_FILES = "Файли GGUF (*.gguf)" self.DAT_FILES = "Файли DAT (*.dat)" self.JSON_FILES = "Файли JSON (*.json)" self.FAILED_LOAD_PRESET = "Не вдалося завантажити пресет: {0}" self.INITIALIZING_AUTOGGUF = "Ініціалізація програми AutoGGUF" self.AUTOGGUF_INITIALIZATION_COMPLETE = "Ініціалізація AutoGGUF завершена" self.REFRESHING_BACKENDS = "Оновлення бекендів" self.NO_BACKENDS_AVAILABLE = "Бекенди недоступні" self.FOUND_VALID_BACKENDS = "Знайдено {0} дійсних бекендів" self.SAVING_PRESET = "Збереження пресета" self.PRESET_SAVED_TO = "Пресет збережено в {0}" self.LOADING_PRESET = "Завантаження пресета" self.PRESET_LOADED_FROM = "Пресет завантажено з {0}" self.ADDING_KV_OVERRIDE = "Додавання KV перевизначення: {0}" self.SAVING_TASK_PRESET = "Збереження пресета завдання для {0}" self.TASK_PRESET_SAVED = "Пресет завдання збережено" self.TASK_PRESET_SAVED_TO = "Пресет завдання збережено в {0}" self.RESTARTING_TASK = "Перезапуск завдання: {0}" self.IN_PROGRESS = "В процесі" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "Завантаження завершено. Витягнуто в: {0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "Бінарний файл llama.cpp завантажено та витягнуто в {0}\nФайли CUDA витягнуто в {1}" self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "Підходящий бекенд CUDA для витягнення не знайдено" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "Бінарний файл llama.cpp завантажено та витягнуто в {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "Оновлення релізів llama.cpp" self.UPDATING_ASSET_LIST = "Оновлення списку активів" self.UPDATING_CUDA_OPTIONS = "Оновлення параметрів CUDA" self.STARTING_LLAMACPP_DOWNLOAD = "Початок завантаження llama.cpp" self.UPDATING_CUDA_BACKENDS = "Оновлення бекендів CUDA" self.NO_CUDA_BACKEND_SELECTED = "Бекенд CUDA для витягнення не вибрано" self.EXTRACTING_CUDA_FILES = "Витягнення файлів CUDA з {0} в {1}" self.DOWNLOAD_ERROR = "Помилка завантаження: {0}" self.SHOWING_TASK_CONTEXT_MENU = "Відображення контекстного меню завдання" self.SHOWING_PROPERTIES_FOR_TASK = "Відображення властивостей завдання: {0}" self.CANCELLING_TASK = "Скасування завдання: {0}" self.CANCELED = "Скасовано" self.DELETING_TASK = "Видалення завдання: {0}" self.LOADING_MODELS = "Завантаження моделей" self.LOADED_MODELS = "Завантажено {0} моделей" self.BROWSING_FOR_MODELS_DIRECTORY = "Пошук каталогу моделей" self.SELECT_MODELS_DIRECTORY = "Виберіть каталог моделей" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Пошук вихідного каталогу" self.SELECT_OUTPUT_DIRECTORY = "Виберіть вихідний каталог" self.BROWSING_FOR_LOGS_DIRECTORY = "Пошук каталогу логів" self.SELECT_LOGS_DIRECTORY = "Виберіть каталог логів" self.BROWSING_FOR_IMATRIX_FILE = "Пошук файлу IMatrix" self.SELECT_IMATRIX_FILE = "Виберіть файл IMatrix" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} МБ / {2} МБ)" self.CPU_USAGE_FORMAT = "Використання ЦП: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "Перевірка вхідних даних квантування" self.MODELS_PATH_REQUIRED = "Потрібен шлях до моделей" self.OUTPUT_PATH_REQUIRED = "Потрібен шлях виводу" self.LOGS_PATH_REQUIRED = "Потрібен шлях до логів" self.STARTING_MODEL_QUANTIZATION = "Початок квантування моделі" self.INPUT_FILE_NOT_EXIST = "Вхідний файл '{0}' не існує." self.QUANTIZING_MODEL_TO = "Квантування {0} в {1}" self.QUANTIZATION_TASK_STARTED = "Завдання квантування запущено для {0}" self.ERROR_STARTING_QUANTIZATION = "Помилка запуску квантування: {0}" self.UPDATING_MODEL_INFO = "Оновлення інформації про модель: {0}" self.TASK_FINISHED = "Завдання завершено: {0}" self.SHOWING_TASK_DETAILS_FOR = "Відображення відомостей про завдання для: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "Пошук файлу даних IMatrix" self.SELECT_DATA_FILE = "Виберіть файл даних" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "Пошук файлу моделі IMatrix" self.SELECT_MODEL_FILE = "Виберіть файл моделі" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "Пошук вихідного файлу IMatrix" self.SELECT_OUTPUT_FILE = "Виберіть вихідний файл" self.STARTING_IMATRIX_GENERATION = "Початок генерації IMatrix" self.BACKEND_PATH_NOT_EXIST = "Шлях бекенда не існує: {0}" self.GENERATING_IMATRIX = "Генерація IMatrix" self.ERROR_STARTING_IMATRIX_GENERATION = ( "Помилка запуску генерації IMatrix: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "Завдання генерації IMatrix запущено" self.ERROR_MESSAGE = "Помилка: {0}" self.TASK_ERROR = "Помилка завдання: {0}" self.APPLICATION_CLOSING = "Закриття програми" self.APPLICATION_CLOSED = "Програма закрита" self.SELECT_QUANTIZATION_TYPE = "Виберіть тип квантування" self.ALLOWS_REQUANTIZING = ( "Дозволяє переквантувати тензори, які вже були квантовані" ) self.LEAVE_OUTPUT_WEIGHT = "Залишить output.weight не (пере)квантованим" self.DISABLE_K_QUANT_MIXTURES = ( "Вимкнути k-квантові суміші та квантувати всі тензори до одного типу" ) self.USE_DATA_AS_IMPORTANCE_MATRIX = "Використовувати дані у файлі як матрицю важливості для оптимізації квантування" self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Використовувати матрицю важливості для цих тензорів" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Не використовувати матрицю важливості для цих тензорів" ) self.OUTPUT_TENSOR_TYPE = "Тип вихідного тензора:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Використовувати цей тип для тензора output.weight" ) self.TOKEN_EMBEDDING_TYPE = "Тип вбудовування токенів:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Використовувати цей тип для тензора вбудовування токенів" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "Генеруватиме квантовану модель у тих самих шардах, що й вхідні дані" ) self.OVERRIDE_MODEL_METADATA = "Перевизначити метадані моделі" self.INPUT_DATA_FILE_FOR_IMATRIX = "Вхідний файл даних для генерації IMatrix" self.MODEL_TO_BE_QUANTIZED = "Модель для квантування" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = ( "Вихідний шлях для згенерованого IMatrix" ) self.HOW_OFTEN_TO_SAVE_IMATRIX = "Як часто зберігати IMatrix" self.SET_GPU_OFFLOAD_VALUE = "Встановити значення розвантаження GPU (-ngl)" self.COMPLETED = "Завершено" self.REFRESH_MODELS = "Оновити моделі" class _Japanese(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (自動GGUFモデル量子化器)" self.RAM_USAGE = "RAM使用量:" self.CPU_USAGE = "CPU使用率:" self.BACKEND = "Llama.cppバックエンド:" self.REFRESH_BACKENDS = "バックエンドを更新" self.MODELS_PATH = "モデルパス:" self.OUTPUT_PATH = "出力パス:" self.LOGS_PATH = "ログパス:" self.BROWSE = "参照" self.AVAILABLE_MODELS = "利用可能なモデル:" self.QUANTIZATION_TYPE = "量子化タイプ:" self.ALLOW_REQUANTIZE = "再量子化を許可" self.LEAVE_OUTPUT_TENSOR = "出力テンソルを残す" self.PURE = "純粋" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "重みを含める:" self.EXCLUDE_WEIGHTS = "重みを含めない:" self.USE_OUTPUT_TENSOR_TYPE = "出力テンソルタイプを使用" self.USE_TOKEN_EMBEDDING_TYPE = "トークン埋め込みタイプを使用" self.KEEP_SPLIT = "分割を維持" self.KV_OVERRIDES = "KVオーバーライド:" self.ADD_NEW_OVERRIDE = "新しいオーバーライドを追加" self.QUANTIZE_MODEL = "モデルを量子化" self.SAVE_PRESET = "プリセットを保存" self.LOAD_PRESET = "プリセットを読み込む" self.TASKS = "タスク:" self.DOWNLOAD_LLAMACPP = "llama.cppをダウンロード" self.SELECT_RELEASE = "リリースを選択:" self.SELECT_ASSET = "アセットを選択:" self.EXTRACT_CUDA_FILES = "CUDAファイルを抽出" self.SELECT_CUDA_BACKEND = "CUDAバックエンドを選択:" self.DOWNLOAD = "ダウンロード" self.IMATRIX_GENERATION = "IMatrix生成" self.DATA_FILE = "データファイル:" self.MODEL = "モデル:" self.OUTPUT = "出力:" self.OUTPUT_FREQUENCY = "出力頻度:" self.GPU_OFFLOAD = "GPUオフロード:" self.AUTO = "自動" self.GENERATE_IMATRIX = "IMatrixを生成" self.ERROR = "エラー" self.WARNING = "警告" self.PROPERTIES = "プロパティ" self.CANCEL = "キャンセル" self.RESTART = "再起動" self.DELETE = "削除" self.CONFIRM_DELETION = "このタスクを削除してもよろしいですか?" self.TASK_RUNNING_WARNING = ( "一部のタスクはまだ実行中です。終了してもよろしいですか?" ) self.YES = "はい" self.NO = "いいえ" self.DOWNLOAD_COMPLETE = "ダウンロード完了" self.CUDA_EXTRACTION_FAILED = "CUDA抽出に失敗しました" self.PRESET_SAVED = "プリセットが保存されました" self.PRESET_LOADED = "プリセットが読み込まれました" self.NO_ASSET_SELECTED = "アセットが選択されていません" self.DOWNLOAD_FAILED = "ダウンロードに失敗しました" self.NO_BACKEND_SELECTED = "バックエンドが選択されていません" self.NO_MODEL_SELECTED = "モデルが選択されていません" self.REFRESH_RELEASES = "リリースを更新" self.NO_SUITABLE_CUDA_BACKENDS = "適切なCUDAバックエンドが見つかりませんでした" self.LLAMACPP_DOWNLOADED_EXTRACTED = "llama.cppバイナリがダウンロードされ、{0}に抽出されました\nCUDAファイルは{1}に抽出されました" self.CUDA_FILES_EXTRACTED = "CUDAファイルはに抽出されました" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "抽出に適したCUDAバックエンドが見つかりませんでした" ) self.ERROR_FETCHING_RELEASES = "リリースの取得中にエラーが発生しました: {0}" self.CONFIRM_DELETION_TITLE = "削除の確認" self.LOG_FOR = "{0}のログ" self.ALL_FILES = "すべてのファイル (*)" self.GGUF_FILES = "GGUFファイル (*.gguf)" self.DAT_FILES = "DATファイル (*.dat)" self.JSON_FILES = "JSONファイル (*.json)" self.FAILED_LOAD_PRESET = "プリセットの読み込みに失敗しました: {0}" self.INITIALIZING_AUTOGGUF = "AutoGGUFアプリケーションを初期化しています" self.AUTOGGUF_INITIALIZATION_COMPLETE = "AutoGGUFの初期化が完了しました" self.REFRESHING_BACKENDS = "バックエンドを更新しています" self.NO_BACKENDS_AVAILABLE = "利用可能なバックエンドがありません" self.FOUND_VALID_BACKENDS = "{0}個の有効なバックエンドが見つかりました" self.SAVING_PRESET = "プリセットを保存しています" self.PRESET_SAVED_TO = "プリセットは{0}に保存されました" self.LOADING_PRESET = "プリセットを読み込んでいます" self.PRESET_LOADED_FROM = "{0}からプリセットが読み込まれました" self.ADDING_KV_OVERRIDE = "KVオーバーライドを追加しています: {0}" self.SAVING_TASK_PRESET = "{0}のタスクプリセットを保存しています" self.TASK_PRESET_SAVED = "タスクプリセットが保存されました" self.TASK_PRESET_SAVED_TO = "タスクプリセットは{0}に保存されました" self.RESTARTING_TASK = "タスクを再起動しています: {0}" self.IN_PROGRESS = "処理中" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "ダウンロードが完了しました。抽出先: {0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "llama.cppバイナリがダウンロードされ、{0}に抽出されました\nCUDAファイルは{1}に抽出されました" self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "抽出に適したCUDAバックエンドが見つかりませんでした" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "llama.cppバイナリがダウンロードされ、{0}に抽出されました" ) self.REFRESHING_LLAMACPP_RELEASES = "llama.cppリリースを更新しています" self.UPDATING_ASSET_LIST = "アセットリストを更新しています" self.UPDATING_CUDA_OPTIONS = "CUDAオプションを更新しています" self.STARTING_LLAMACPP_DOWNLOAD = "llama.cppのダウンロードを開始しています" self.UPDATING_CUDA_BACKENDS = "CUDAバックエンドを更新しています" self.NO_CUDA_BACKEND_SELECTED = "抽出にCUDAバックエンドが選択されていません" self.EXTRACTING_CUDA_FILES = "{0}から{1}にCUDAファイルを抽出しています" self.DOWNLOAD_ERROR = "ダウンロードエラー: {0}" self.SHOWING_TASK_CONTEXT_MENU = "タスクコンテキストメニューを表示しています" self.SHOWING_PROPERTIES_FOR_TASK = "タスクのプロパティを表示しています: {0}" self.CANCELLING_TASK = "タスクをキャンセルしています: {0}" self.CANCELED = "キャンセル済み" self.DELETING_TASK = "タスクを削除しています: {0}" self.LOADING_MODELS = "モデルを読み込んでいます" self.LOADED_MODELS = "{0}個のモデルが読み込まれました" self.BROWSING_FOR_MODELS_DIRECTORY = "モデルディレクトリを参照しています" self.SELECT_MODELS_DIRECTORY = "モデルディレクトリを選択" self.BROWSING_FOR_OUTPUT_DIRECTORY = "出力ディレクトリを参照しています" self.SELECT_OUTPUT_DIRECTORY = "出力ディレクトリを選択" self.BROWSING_FOR_LOGS_DIRECTORY = "ログディレクトリを参照しています" self.SELECT_LOGS_DIRECTORY = "ログディレクトリを選択" self.BROWSING_FOR_IMATRIX_FILE = "IMatrixファイルを参照しています" self.SELECT_IMATRIX_FILE = "IMatrixファイルを選択" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "CPU使用率: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "量子化入力を検証しています" self.MODELS_PATH_REQUIRED = "モデルパスが必要です" self.OUTPUT_PATH_REQUIRED = "出力パスが必要です" self.LOGS_PATH_REQUIRED = "ログパスが必要です" self.STARTING_MODEL_QUANTIZATION = "モデルの量子化を開始しています" self.INPUT_FILE_NOT_EXIST = "入力ファイル '{0}' は存在しません。" self.QUANTIZING_MODEL_TO = "{0} を {1} に量子化しています" self.QUANTIZATION_TASK_STARTED = "{0} の量子化タスクが開始されました" self.ERROR_STARTING_QUANTIZATION = "量子化の開始中にエラーが発生しました: {0}" self.UPDATING_MODEL_INFO = "モデル情報を更新しています: {0}" self.TASK_FINISHED = "タスクが完了しました: {0}" self.SHOWING_TASK_DETAILS_FOR = "タスクの詳細を表示しています: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "IMatrixデータファイルを参照しています" self.SELECT_DATA_FILE = "データファイルを選択" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "IMatrixモデルファイルを参照しています" self.SELECT_MODEL_FILE = "モデルファイルを選択" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "IMatrix出力ファイルを参照しています" self.SELECT_OUTPUT_FILE = "出力ファイルを選択" self.STARTING_IMATRIX_GENERATION = "IMatrixの生成を開始しています" self.BACKEND_PATH_NOT_EXIST = "バックエンドパスが存在しません: {0}" self.GENERATING_IMATRIX = "IMatrixを生成しています" self.ERROR_STARTING_IMATRIX_GENERATION = ( "IMatrixの生成を開始中にエラーが発生しました: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "IMatrix生成タスクが開始されました" self.ERROR_MESSAGE = "エラー: {0}" self.TASK_ERROR = "タスクエラー: {0}" self.APPLICATION_CLOSING = "アプリケーションを終了しています" self.APPLICATION_CLOSED = "アプリケーションが終了しました" self.SELECT_QUANTIZATION_TYPE = "量子化タイプを選択してください" self.ALLOWS_REQUANTIZING = ( "すでに量子化されているテンソルの再量子化を許可します" ) self.LEAVE_OUTPUT_WEIGHT = "output.weightは(再)量子化されません" self.DISABLE_K_QUANT_MIXTURES = ( "k-quant混合を無効にし、すべてのテンソルを同じタイプに量子化します" ) self.USE_DATA_AS_IMPORTANCE_MATRIX = ( "量子化最適化の重要度マトリックスとしてファイル内のデータを使用します" ) self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "これらのテンソルに重要度マトリックスを使用します" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "これらのテンソルに重要度マトリックスを使用しません" ) self.OUTPUT_TENSOR_TYPE = "出力テンソルタイプ:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "output.weightテンソルにこのタイプを使用します" ) self.TOKEN_EMBEDDING_TYPE = "トークン埋め込みタイプ:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "トークン埋め込みテンソルにこのタイプを使用します" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "入力と同じシャードで量子化されたモデルを生成します" ) self.OVERRIDE_MODEL_METADATA = "モデルメタデータを上書きする" self.INPUT_DATA_FILE_FOR_IMATRIX = "IMatrix生成用の入力データファイル" self.MODEL_TO_BE_QUANTIZED = "量子化されるモデル" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = "生成されたIMatrixの出力パス" self.HOW_OFTEN_TO_SAVE_IMATRIX = "IMatrixを保存する頻度" self.SET_GPU_OFFLOAD_VALUE = "GPUオフロード値を設定 (-ngl)" self.COMPLETED = "完了しました" self.REFRESH_MODELS = "モデルを更新" class _German(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (automatisierter GGUF-Modellquantisierer)" self.RAM_USAGE = "RAM-Nutzung:" self.CPU_USAGE = "CPU-Auslastung:" self.BACKEND = "Llama.cpp-Backend:" self.REFRESH_BACKENDS = "Backends aktualisieren" self.MODELS_PATH = "Modelle Pfad:" self.OUTPUT_PATH = "Ausgabepfad:" self.LOGS_PATH = "Log-Pfad:" self.BROWSE = "Durchsuchen" self.AVAILABLE_MODELS = "Verfügbare Modelle:" self.QUANTIZATION_TYPE = "Quantisierungstyp:" self.ALLOW_REQUANTIZE = "Requantisierung zulassen" self.LEAVE_OUTPUT_TENSOR = "Ausgabetensor belassen" self.PURE = "Rein" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "Gewichte einschließen:" self.EXCLUDE_WEIGHTS = "Gewichte ausschließen:" self.USE_OUTPUT_TENSOR_TYPE = "Ausgabetensortyp verwenden" self.USE_TOKEN_EMBEDDING_TYPE = "Token-Einbettungstyp verwenden" self.KEEP_SPLIT = "Aufteilung beibehalten" self.KV_OVERRIDES = "KV-Überschreibungen:" self.ADD_NEW_OVERRIDE = "Neue Überschreibung hinzufügen" self.QUANTIZE_MODEL = "Modell quantisieren" self.SAVE_PRESET = "Preset speichern" self.LOAD_PRESET = "Preset laden" self.TASKS = "Aufgaben:" self.DOWNLOAD_LLAMACPP = "llama.cpp herunterladen" self.SELECT_RELEASE = "Release auswählen:" self.SELECT_ASSET = "Asset auswählen:" self.EXTRACT_CUDA_FILES = "CUDA-Dateien extrahieren" self.SELECT_CUDA_BACKEND = "CUDA-Backend auswählen:" self.DOWNLOAD = "Herunterladen" self.IMATRIX_GENERATION = "IMatrix-Generierung" self.DATA_FILE = "Datendatei:" self.MODEL = "Modell:" self.OUTPUT = "Ausgabe:" self.OUTPUT_FREQUENCY = "Ausgabefrequenz:" self.GPU_OFFLOAD = "GPU-Offload:" self.AUTO = "Auto" self.GENERATE_IMATRIX = "IMatrix generieren" self.ERROR = "Fehler" self.WARNING = "Warnung" self.PROPERTIES = "Eigenschaften" self.CANCEL = "Abbrechen" self.RESTART = "Neustart" self.DELETE = "Löschen" self.CONFIRM_DELETION = ( "Sind Sie sicher, dass Sie diese Aufgabe löschen möchten?" ) self.TASK_RUNNING_WARNING = ( "Einige Aufgaben laufen noch. Möchten Sie wirklich beenden?" ) self.YES = "Ja" self.NO = "Nein" self.DOWNLOAD_COMPLETE = "Download abgeschlossen" self.CUDA_EXTRACTION_FAILED = "CUDA-Extraktion fehlgeschlagen" self.PRESET_SAVED = "Preset gespeichert" self.PRESET_LOADED = "Preset geladen" self.NO_ASSET_SELECTED = "Kein Asset ausgewählt" self.DOWNLOAD_FAILED = "Download fehlgeschlagen" self.NO_BACKEND_SELECTED = "Kein Backend ausgewählt" self.NO_MODEL_SELECTED = "Kein Modell ausgewählt" self.REFRESH_RELEASES = "Releases aktualisieren" self.NO_SUITABLE_CUDA_BACKENDS = "Keine geeigneten CUDA-Backends gefunden" self.LLAMACPP_DOWNLOADED_EXTRACTED = "llama.cpp-Binärdatei heruntergeladen und extrahiert nach {0}\nCUDA-Dateien extrahiert nach {1}" self.CUDA_FILES_EXTRACTED = "CUDA-Dateien extrahiert nach" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "Kein geeignetes CUDA-Backend für die Extraktion gefunden" ) self.ERROR_FETCHING_RELEASES = "Fehler beim Abrufen der Releases: {0}" self.CONFIRM_DELETION_TITLE = "Löschen bestätigen" self.LOG_FOR = "Log für {0}" self.ALL_FILES = "Alle Dateien (*)" self.GGUF_FILES = "GGUF-Dateien (*.gguf)" self.DAT_FILES = "DAT-Dateien (*.dat)" self.JSON_FILES = "JSON-Dateien (*.json)" self.FAILED_LOAD_PRESET = "Preset konnte nicht geladen werden: {0}" self.INITIALIZING_AUTOGGUF = "AutoGGUF-Anwendung wird initialisiert" self.AUTOGGUF_INITIALIZATION_COMPLETE = "AutoGGUF-Initialisierung abgeschlossen" self.REFRESHING_BACKENDS = "Backends werden aktualisiert" self.NO_BACKENDS_AVAILABLE = "Keine Backends verfügbar" self.FOUND_VALID_BACKENDS = "{0} gültige Backends gefunden" self.SAVING_PRESET = "Preset wird gespeichert" self.PRESET_SAVED_TO = "Preset gespeichert unter {0}" self.LOADING_PRESET = "Preset wird geladen" self.PRESET_LOADED_FROM = "Preset von {0} geladen" self.ADDING_KV_OVERRIDE = "KV-Überschreibung wird hinzugefügt: {0}" self.SAVING_TASK_PRESET = "Task-Preset für {0} wird gespeichert" self.TASK_PRESET_SAVED = "Task-Preset gespeichert" self.TASK_PRESET_SAVED_TO = "Task-Preset gespeichert unter {0}" self.RESTARTING_TASK = "Aufgabe wird neu gestartet: {0}" self.IN_PROGRESS = "In Bearbeitung" self.DOWNLOAD_FINISHED_EXTRACTED_TO = ( "Download abgeschlossen. Extrahiert nach: {0}" ) self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "llama.cpp-Binärdatei heruntergeladen und extrahiert nach {0}\nCUDA-Dateien extrahiert nach {1}" self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "Kein geeignetes CUDA-Backend für die Extraktion gefunden" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "llama.cpp-Binärdatei heruntergeladen und extrahiert nach {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "llama.cpp-Releases werden aktualisiert" self.UPDATING_ASSET_LIST = "Asset-Liste wird aktualisiert" self.UPDATING_CUDA_OPTIONS = "CUDA-Optionen werden aktualisiert" self.STARTING_LLAMACPP_DOWNLOAD = "Download von llama.cpp wird gestartet" self.UPDATING_CUDA_BACKENDS = "CUDA-Backends werden aktualisiert" self.NO_CUDA_BACKEND_SELECTED = ( "Kein CUDA-Backend für die Extraktion ausgewählt" ) self.EXTRACTING_CUDA_FILES = "CUDA-Dateien werden von {0} nach {1} extrahiert" self.DOWNLOAD_ERROR = "Download-Fehler: {0}" self.SHOWING_TASK_CONTEXT_MENU = "Kontextmenü der Aufgabe wird angezeigt" self.SHOWING_PROPERTIES_FOR_TASK = ( "Eigenschaften für Aufgabe werden angezeigt: {0}" ) self.CANCELLING_TASK = "Aufgabe wird abgebrochen: {0}" self.CANCELED = "Abgebrochen" self.DELETING_TASK = "Aufgabe wird gelöscht: {0}" self.LOADING_MODELS = "Modelle werden geladen" self.LOADED_MODELS = "{0} Modelle geladen" self.BROWSING_FOR_MODELS_DIRECTORY = "Modelle-Verzeichnis wird durchsucht" self.SELECT_MODELS_DIRECTORY = "Modelle-Verzeichnis auswählen" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Ausgabeverzeichnis wird durchsucht" self.SELECT_OUTPUT_DIRECTORY = "Ausgabeverzeichnis auswählen" self.BROWSING_FOR_LOGS_DIRECTORY = "Log-Verzeichnis wird durchsucht" self.SELECT_LOGS_DIRECTORY = "Log-Verzeichnis auswählen" self.BROWSING_FOR_IMATRIX_FILE = "IMatrix-Datei wird durchsucht" self.SELECT_IMATRIX_FILE = "IMatrix-Datei auswählen" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "CPU-Auslastung: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "Quantisierungseingaben werden validiert" self.MODELS_PATH_REQUIRED = "Modelle-Pfad ist erforderlich" self.OUTPUT_PATH_REQUIRED = "Ausgabepfad ist erforderlich" self.LOGS_PATH_REQUIRED = "Log-Pfad ist erforderlich" self.STARTING_MODEL_QUANTIZATION = "Modellquantisierung wird gestartet" self.INPUT_FILE_NOT_EXIST = "Die Eingabedatei '{0}' existiert nicht." self.QUANTIZING_MODEL_TO = "Quantisierung von {0} zu {1}" self.QUANTIZATION_TASK_STARTED = "Quantisierungsaufgabe für {0} gestartet" self.ERROR_STARTING_QUANTIZATION = "Fehler beim Starten der Quantisierung: {0}" self.UPDATING_MODEL_INFO = "Modellinformationen werden aktualisiert: {0}" self.TASK_FINISHED = "Aufgabe abgeschlossen: {0}" self.SHOWING_TASK_DETAILS_FOR = "Aufgabendetails werden angezeigt für: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "IMatrix-Datendatei wird durchsucht" self.SELECT_DATA_FILE = "Datendatei auswählen" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "IMatrix-Modelldatei wird durchsucht" self.SELECT_MODEL_FILE = "Modelldatei auswählen" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "IMatrix-Ausgabedatei wird durchsucht" self.SELECT_OUTPUT_FILE = "Ausgabedatei auswählen" self.STARTING_IMATRIX_GENERATION = "IMatrix-Generierung wird gestartet" self.BACKEND_PATH_NOT_EXIST = "Backend-Pfad existiert nicht: {0}" self.GENERATING_IMATRIX = "IMatrix wird generiert" self.ERROR_STARTING_IMATRIX_GENERATION = ( "Fehler beim Starten der IMatrix-Generierung: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "IMatrix-Generierungsaufgabe gestartet" self.ERROR_MESSAGE = "Fehler: {0}" self.TASK_ERROR = "Aufgabenfehler: {0}" self.APPLICATION_CLOSING = "Anwendung wird geschlossen" self.APPLICATION_CLOSED = "Anwendung geschlossen" self.SELECT_QUANTIZATION_TYPE = "Wählen Sie den Quantisierungstyp aus" self.ALLOWS_REQUANTIZING = "Ermöglicht die Requantisierung von Tensoren, die bereits quantisiert wurden" self.LEAVE_OUTPUT_WEIGHT = "Lässt output.weight nicht (re)quantisiert" self.DISABLE_K_QUANT_MIXTURES = "Deaktivieren Sie k-Quant-Mischungen und quantisieren Sie alle Tensoren auf denselben Typ" self.USE_DATA_AS_IMPORTANCE_MATRIX = "Verwenden Sie Daten in der Datei als Wichtigkeitsmatrix für Quant-Optimierungen" self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Verwenden Sie die Wichtigkeitsmatrix für diese Tensoren" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Verwenden Sie die Wichtigkeitsmatrix nicht für diese Tensoren" ) self.OUTPUT_TENSOR_TYPE = "Ausgabetensortyp:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Verwenden Sie diesen Typ für den output.weight-Tensor" ) self.TOKEN_EMBEDDING_TYPE = "Token-Einbettungstyp:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Verwenden Sie diesen Typ für den Token-Einbettungstensor" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "Generiert ein quantisiertes Modell in denselben Shards wie die Eingabe" ) self.OVERRIDE_MODEL_METADATA = "Modellmetadaten überschreiben" self.INPUT_DATA_FILE_FOR_IMATRIX = ( "Eingabedatendatei für die IMatrix-Generierung" ) self.MODEL_TO_BE_QUANTIZED = "Zu quantisierendes Modell" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = ( "Ausgabepfad für die generierte IMatrix" ) self.HOW_OFTEN_TO_SAVE_IMATRIX = "Wie oft die IMatrix gespeichert werden soll" self.SET_GPU_OFFLOAD_VALUE = "GPU-Offload-Wert festlegen (-ngl)" self.COMPLETED = "Abgeschlossen" self.REFRESH_MODELS = "Modelle aktualisieren" class _Portuguese(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (Quantizador Automático de Modelos GGUF)" self.RAM_USAGE = "Uso de RAM:" self.CPU_USAGE = "Uso da CPU:" self.BACKEND = "Backend do Llama.cpp:" self.REFRESH_BACKENDS = "Atualizar Backends" self.MODELS_PATH = "Caminho dos Modelos:" self.OUTPUT_PATH = "Caminho de Saída:" self.LOGS_PATH = "Caminho dos Logs:" self.BROWSE = "Navegar" self.AVAILABLE_MODELS = "Modelos Disponíveis:" self.QUANTIZATION_TYPE = "Tipo de Quantização:" self.ALLOW_REQUANTIZE = "Permitir Requantização" self.LEAVE_OUTPUT_TENSOR = "Manter Tensor de Saída" self.PURE = "Puro" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "Incluir Pesos:" self.EXCLUDE_WEIGHTS = "Excluir Pesos:" self.USE_OUTPUT_TENSOR_TYPE = "Usar Tipo de Tensor de Saída" self.USE_TOKEN_EMBEDDING_TYPE = "Usar Tipo de Incorporação de Token" self.KEEP_SPLIT = "Manter Divisão" self.KV_OVERRIDES = "Substituições KV:" self.ADD_NEW_OVERRIDE = "Adicionar Nova Substituição" self.QUANTIZE_MODEL = "Quantizar Modelo" self.SAVE_PRESET = "Salvar Predefinição" self.LOAD_PRESET = "Carregar Predefinição" self.TASKS = "Tarefas:" self.DOWNLOAD_LLAMACPP = "Baixar llama.cpp" self.SELECT_RELEASE = "Selecionar Versão:" self.SELECT_ASSET = "Selecionar Ativo:" self.EXTRACT_CUDA_FILES = "Extrair Arquivos CUDA" self.SELECT_CUDA_BACKEND = "Selecionar Backend CUDA:" self.DOWNLOAD = "Baixar" self.IMATRIX_GENERATION = "Geração de IMatrix" self.DATA_FILE = "Arquivo de Dados:" self.MODEL = "Modelo:" self.OUTPUT = "Saída:" self.OUTPUT_FREQUENCY = "Frequência de Saída:" self.GPU_OFFLOAD = "Offload da GPU:" self.AUTO = "Automático" self.GENERATE_IMATRIX = "Gerar IMatrix" self.ERROR = "Erro" self.WARNING = "Aviso" self.PROPERTIES = "Propriedades" self.CANCEL = "Cancelar" self.RESTART = "Reiniciar" self.DELETE = "Excluir" self.CONFIRM_DELETION = "Tem certeza de que deseja excluir esta tarefa?" self.TASK_RUNNING_WARNING = ( "Algumas tarefas ainda estão em execução. Tem certeza de que deseja sair?" ) self.YES = "Sim" self.NO = "Não" self.DOWNLOAD_COMPLETE = "Download Concluído" self.CUDA_EXTRACTION_FAILED = "Falha na Extração do CUDA" self.PRESET_SAVED = "Predefinição Salva" self.PRESET_LOADED = "Predefinição Carregada" self.NO_ASSET_SELECTED = "Nenhum ativo selecionado" self.DOWNLOAD_FAILED = "Falha no download" self.NO_BACKEND_SELECTED = "Nenhum backend selecionado" self.NO_MODEL_SELECTED = "Nenhum modelo selecionado" self.REFRESH_RELEASES = "Atualizar Versões" self.NO_SUITABLE_CUDA_BACKENDS = "Nenhum backend CUDA adequado encontrado" self.LLAMACPP_DOWNLOADED_EXTRACTED = "Binário llama.cpp baixado e extraído para {0}\nArquivos CUDA extraídos para {1}" self.CUDA_FILES_EXTRACTED = "Arquivos CUDA extraídos para" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "Nenhum backend CUDA adequado encontrado para extração" ) self.ERROR_FETCHING_RELEASES = "Erro ao buscar versões: {0}" self.CONFIRM_DELETION_TITLE = "Confirmar Exclusão" self.LOG_FOR = "Log para {0}" self.ALL_FILES = "Todos os Arquivos (*)" self.GGUF_FILES = "Arquivos GGUF (*.gguf)" self.DAT_FILES = "Arquivos DAT (*.dat)" self.JSON_FILES = "Arquivos JSON (*.json)" self.FAILED_LOAD_PRESET = "Falha ao carregar a predefinição: {0}" self.INITIALIZING_AUTOGGUF = "Inicializando o aplicativo AutoGGUF" self.AUTOGGUF_INITIALIZATION_COMPLETE = "Inicialização do AutoGGUF concluída" self.REFRESHING_BACKENDS = "Atualizando backends" self.NO_BACKENDS_AVAILABLE = "Nenhum backend disponível" self.FOUND_VALID_BACKENDS = "{0} backends válidos encontrados" self.SAVING_PRESET = "Salvando predefinição" self.PRESET_SAVED_TO = "Predefinição salva em {0}" self.LOADING_PRESET = "Carregando predefinição" self.PRESET_LOADED_FROM = "Predefinição carregada de {0}" self.ADDING_KV_OVERRIDE = "Adicionando substituição KV: {0}" self.SAVING_TASK_PRESET = "Salvando predefinição de tarefa para {0}" self.TASK_PRESET_SAVED = "Predefinição de Tarefa Salva" self.TASK_PRESET_SAVED_TO = "Predefinição de tarefa salva em {0}" self.RESTARTING_TASK = "Reiniciando tarefa: {0}" self.IN_PROGRESS = "Em Andamento" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "Download concluído. Extraído para: {0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "Binário llama.cpp baixado e extraído para {0}\nArquivos CUDA extraídos para {1}" self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "Nenhum backend CUDA adequado encontrado para extração" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "Binário llama.cpp baixado e extraído para {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "Atualizando versões do llama.cpp" self.UPDATING_ASSET_LIST = "Atualizando lista de ativos" self.UPDATING_CUDA_OPTIONS = "Atualizando opções CUDA" self.STARTING_LLAMACPP_DOWNLOAD = "Iniciando download do llama.cpp" self.UPDATING_CUDA_BACKENDS = "Atualizando backends CUDA" self.NO_CUDA_BACKEND_SELECTED = "Nenhum backend CUDA selecionado para extração" self.EXTRACTING_CUDA_FILES = "Extraindo arquivos CUDA de {0} para {1}" self.DOWNLOAD_ERROR = "Erro de download: {0}" self.SHOWING_TASK_CONTEXT_MENU = "Exibindo menu de contexto da tarefa" self.SHOWING_PROPERTIES_FOR_TASK = "Exibindo propriedades para a tarefa: {0}" self.CANCELLING_TASK = "Cancelando tarefa: {0}" self.CANCELED = "Cancelado" self.DELETING_TASK = "Excluindo tarefa: {0}" self.LOADING_MODELS = "Carregando modelos" self.LOADED_MODELS = "{0} modelos carregados" self.BROWSING_FOR_MODELS_DIRECTORY = "Navegando pelo diretório de modelos" self.SELECT_MODELS_DIRECTORY = "Selecionar Diretório de Modelos" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Navegando pelo diretório de saída" self.SELECT_OUTPUT_DIRECTORY = "Selecionar Diretório de Saída" self.BROWSING_FOR_LOGS_DIRECTORY = "Navegando pelo diretório de logs" self.SELECT_LOGS_DIRECTORY = "Selecionar Diretório de Logs" self.BROWSING_FOR_IMATRIX_FILE = "Navegando pelo arquivo IMatrix" self.SELECT_IMATRIX_FILE = "Selecionar Arquivo IMatrix" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "Uso da CPU: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "Validando entradas de quantização" self.MODELS_PATH_REQUIRED = "O caminho dos modelos é obrigatório" self.OUTPUT_PATH_REQUIRED = "O caminho de saída é obrigatório" self.LOGS_PATH_REQUIRED = "O caminho dos logs é obrigatório" self.STARTING_MODEL_QUANTIZATION = "Iniciando a quantização do modelo" self.INPUT_FILE_NOT_EXIST = "O arquivo de entrada '{0}' não existe." self.QUANTIZING_MODEL_TO = "Quantizando {0} para {1}" self.QUANTIZATION_TASK_STARTED = "Tarefa de quantização iniciada para {0}" self.ERROR_STARTING_QUANTIZATION = "Erro ao iniciar a quantização: {0}" self.UPDATING_MODEL_INFO = "Atualizando informações do modelo: {0}" self.TASK_FINISHED = "Tarefa concluída: {0}" self.SHOWING_TASK_DETAILS_FOR = "Mostrando detalhes da tarefa para: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "Navegando pelo arquivo de dados IMatrix" self.SELECT_DATA_FILE = "Selecionar Arquivo de Dados" self.BROWSING_FOR_IMATRIX_MODEL_FILE = ( "Navegando pelo arquivo de modelo IMatrix" ) self.SELECT_MODEL_FILE = "Selecionar Arquivo de Modelo" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = ( "Navegando pelo arquivo de saída IMatrix" ) self.SELECT_OUTPUT_FILE = "Selecionar Arquivo de Saída" self.STARTING_IMATRIX_GENERATION = "Iniciando a geração de IMatrix" self.BACKEND_PATH_NOT_EXIST = "O caminho do backend não existe: {0}" self.GENERATING_IMATRIX = "Gerando IMatrix" self.ERROR_STARTING_IMATRIX_GENERATION = ( "Erro ao iniciar a geração de IMatrix: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "Tarefa de geração de IMatrix iniciada" self.ERROR_MESSAGE = "Erro: {0}" self.TASK_ERROR = "Erro de tarefa: {0}" self.APPLICATION_CLOSING = "Fechando o aplicativo" self.APPLICATION_CLOSED = "Aplicativo fechado" self.SELECT_QUANTIZATION_TYPE = "Selecione o tipo de quantização" self.ALLOWS_REQUANTIZING = ( "Permite requantizar tensores que já foram quantizados" ) self.LEAVE_OUTPUT_WEIGHT = "Deixará output.weight não (re)quantizado" self.DISABLE_K_QUANT_MIXTURES = "Desabilitar misturas k-quant e quantizar todos os tensores para o mesmo tipo" self.USE_DATA_AS_IMPORTANCE_MATRIX = "Usar os dados no arquivo como matriz de importância para otimizações de quantização" self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Usar matriz de importância para estes tensores" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Não usar matriz de importância para estes tensores" ) self.OUTPUT_TENSOR_TYPE = "Tipo de Tensor de Saída:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Usar este tipo para o tensor output.weight" ) self.TOKEN_EMBEDDING_TYPE = "Tipo de Incorporação de Token:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Usar este tipo para o tensor de incorporações de token" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "Irá gerar o modelo quantizado nos mesmos shards da entrada" ) self.OVERRIDE_MODEL_METADATA = "Substituir metadados do modelo" self.INPUT_DATA_FILE_FOR_IMATRIX = ( "Arquivo de dados de entrada para geração de IMatrix" ) self.MODEL_TO_BE_QUANTIZED = "Modelo a ser quantizado" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = ( "Caminho de saída para o IMatrix gerado" ) self.HOW_OFTEN_TO_SAVE_IMATRIX = "Com que frequência salvar o IMatrix" self.SET_GPU_OFFLOAD_VALUE = "Definir valor de offload da GPU (-ngl)" self.COMPLETED = "Concluído" self.REFRESH_MODELS = "Atualizar modelos" class _Arabic(_Localization): def __init__(self): super().__init__() # واجهة المستخدم العامة self.WINDOW_TITLE = "AutoGGUF (محول نماذج GGUF الآلي)" self.RAM_USAGE = "استخدام الذاكرة:" self.CPU_USAGE = "استخدام المعالج:" self.BACKEND = "خلفية Llama.cpp:" self.REFRESH_BACKENDS = "تحديث الخلفيات" self.MODELS_PATH = "مسار النماذج:" self.OUTPUT_PATH = "مسار الإخراج:" self.LOGS_PATH = "مسار السجلات:" self.BROWSE = "تصفح" self.AVAILABLE_MODELS = "النماذج المتاحة:" self.REFRESH_MODELS = "تحديث النماذج" # استيراد النموذج self.IMPORT_MODEL = "استيراد نموذج" self.SELECT_MODEL_TO_IMPORT = "اختر النموذج للاستيراد" self.CONFIRM_IMPORT = "تأكيد الاستيراد" self.IMPORT_MODEL_CONFIRMATION = "هل تريد استيراد النموذج {}؟" self.MODEL_IMPORTED_SUCCESSFULLY = "تم استيراد النموذج {} بنجاح" self.IMPORTING_MODEL = "جاري استيراد النموذج" self.IMPORTED_MODEL_TOOLTIP = "النموذج المستورد: {}" # التحقق من GGUF self.INVALID_GGUF_FILE = "ملف GGUF غير صالح: {}" self.SHARDED_MODEL_NAME = "{} (مجزأ)" self.IMPORTED_MODEL_TOOLTIP = "النموذج المستورد: {}" self.CONCATENATED_FILE_WARNING = ( "هذا جزء من ملف مدمج. لن يعمل مع llama-quantize؛ يرجى دمج الملف أولاً." ) self.CONCATENATED_FILES_FOUND = ( "تم العثور على {} أجزاء ملفات مدمجة. يرجى دمج الملفات أولاً." ) # مراقبة وحدة معالجة الرسومات self.GPU_USAGE = "استخدام وحدة معالجة الرسومات:" self.GPU_USAGE_FORMAT = "وحدة معالجة الرسومات: {:.1f}% | ذاكرة الفيديو: {:.1f}% ({} ميجابايت / {} ميجابايت)" self.GPU_DETAILS = "تفاصيل وحدة معالجة الرسومات" self.GPU_USAGE_OVER_TIME = "استخدام وحدة معالجة الرسومات عبر الوقت" self.VRAM_USAGE_OVER_TIME = "استخدام ذاكرة الفيديو عبر الوقت" self.PERCENTAGE = "النسبة المئوية" self.TIME = "الوقت (ثانية)" self.NO_GPU_DETECTED = "لم يتم اكتشاف وحدة معالجة رسومات" self.SELECT_GPU = "اختر وحدة معالجة الرسومات" self.AMD_GPU_NOT_SUPPORTED = ( "تم اكتشاف وحدة معالجة رسومات AMD، لكنها غير مدعومة" ) # التكميم self.QUANTIZATION_TYPE = "نوع التكميم:" self.ALLOW_REQUANTIZE = "السماح بإعادة التكميم" self.LEAVE_OUTPUT_TENSOR = "ترك تنسور الإخراج" self.PURE = "نقي" self.IMATRIX = "مصفوفة الأهمية:" self.INCLUDE_WEIGHTS = "تضمين الأوزان:" self.EXCLUDE_WEIGHTS = "استبعاد الأوزان:" self.USE_OUTPUT_TENSOR_TYPE = "استخدام نوع تنسور الإخراج" self.USE_TOKEN_EMBEDDING_TYPE = "استخدام نوع تضمين الرمز" self.KEEP_SPLIT = "الحفاظ على التقسيم" self.KV_OVERRIDES = "تجاوزات KV:" self.ADD_NEW_OVERRIDE = "إضافة تجاوز جديد" self.QUANTIZE_MODEL = "تكميم النموذج" self.EXTRA_ARGUMENTS = "وسائط إضافية:" self.EXTRA_ARGUMENTS_LABEL = "وسائط سطر الأوامر الإضافية" self.QUANTIZATION_COMMAND = "أمر التكميم" # الإعدادات المسبقة self.SAVE_PRESET = "حفظ الإعداد المسبق" self.LOAD_PRESET = "تحميل الإعداد المسبق" # المهام self.TASKS = "المهام:" # تنزيل llama.cpp self.DOWNLOAD_LLAMACPP = "تنزيل llama.cpp" self.SELECT_RELEASE = "اختر الإصدار:" self.SELECT_ASSET = "اختر الأصل:" self.EXTRACT_CUDA_FILES = "استخراج ملفات CUDA" self.SELECT_CUDA_BACKEND = "اختر خلفية CUDA:" self.DOWNLOAD = "تنزيل" self.REFRESH_RELEASES = "تحديث الإصدارات" # توليد مصفوفة الأهمية self.IMATRIX_GENERATION = "توليد مصفوفة الأهمية" self.DATA_FILE = "ملف البيانات:" self.MODEL = "النموذج:" self.OUTPUT = "الإخراج:" self.OUTPUT_FREQUENCY = "تردد الإخراج:" self.GPU_OFFLOAD = "تحميل وحدة معالجة الرسومات:" self.AUTO = "تلقائي" self.GENERATE_IMATRIX = "توليد مصفوفة الأهمية" self.CONTEXT_SIZE = "حجم السياق:" self.CONTEXT_SIZE_FOR_IMATRIX = "حجم السياق لتوليد مصفوفة الأهمية" self.THREADS = "عدد المسارات:" self.NUMBER_OF_THREADS_FOR_IMATRIX = "عدد المسارات لتوليد مصفوفة الأهمية" self.IMATRIX_GENERATION_COMMAND = "أمر توليد مصفوفة الأهمية" # تحويل LoRA self.LORA_CONVERSION = "تحويل LoRA" self.LORA_INPUT_PATH = "مسار إدخال LoRA" self.LORA_OUTPUT_PATH = "مسار إخراج LoRA" self.SELECT_LORA_INPUT_DIRECTORY = "اختر مجلد إدخال LoRA" self.SELECT_LORA_OUTPUT_FILE = "اختر ملف إخراج LoRA" self.CONVERT_LORA = "تحويل LoRA" self.LORA_CONVERSION_COMMAND = "أمر تحويل LoRA" # تصدير LoRA self.EXPORT_LORA = "تصدير LoRA" self.GGML_LORA_ADAPTERS = "محولات GGML LoRA" self.SELECT_LORA_ADAPTER_FILES = "اختر ملفات محول LoRA" self.ADD_ADAPTER = "إضافة محول" self.DELETE_ADAPTER = "حذف" self.LORA_SCALE = "مقياس LoRA" self.ENTER_LORA_SCALE_VALUE = "أدخل قيمة مقياس LoRA (اختياري)" self.NUMBER_OF_THREADS_FOR_LORA_EXPORT = "عدد المسارات لتصدير LoRA" self.LORA_EXPORT_COMMAND = "أمر تصدير LoRA" # تحويل HuggingFace إلى GGUF self.HF_TO_GGUF_CONVERSION = "تحويل HuggingFace إلى GGUF" self.MODEL_DIRECTORY = "مجلد النموذج:" self.OUTPUT_FILE = "ملف الإخراج:" self.OUTPUT_TYPE = "نوع الإخراج:" self.VOCAB_ONLY = "المفردات فقط" self.USE_TEMP_FILE = "استخدام ملف مؤقت" self.NO_LAZY_EVALUATION = "بدون تقييم كسول" self.MODEL_NAME = "اسم النموذج:" self.VERBOSE = "مفصل" self.SPLIT_MAX_SIZE = "الحجم الأقصى للتقسيم:" self.DRY_RUN = "تشغيل تجريبي" self.CONVERT_HF_TO_GGUF = "تحويل HF إلى GGUF" self.SELECT_HF_MODEL_DIRECTORY = "اختر مجلد نموذج HuggingFace" self.BROWSE_FOR_HF_MODEL_DIRECTORY = "تصفح مجلد نموذج HuggingFace" self.BROWSE_FOR_HF_TO_GGUF_OUTPUT = "تصفح ملف إخراج تحويل HuggingFace إلى GGUF" # التحقق من التحديثات self.UPDATE_AVAILABLE = "تحديث متاح" self.NEW_VERSION_AVAILABLE = "إصدار جديد متاح: {}" self.DOWNLOAD_NEW_VERSION = "تنزيل؟" self.ERROR_CHECKING_FOR_UPDATES = "خطأ في التحقق من التحديثات:" self.CHECKING_FOR_UPDATES = "جاري التحقق من التحديثات" # رسائل عامة self.ERROR = "خطأ" self.WARNING = "تحذير" self.PROPERTIES = "الخصائص" self.CANCEL = "إلغاء" self.RESTART = "إعادة تشغيل" self.DELETE = "حذف" self.CONFIRM_DELETION = "هل أنت متأكد أنك تريد حذف هذه المهمة؟" self.TASK_RUNNING_WARNING = ( "بعض المهام ما زالت قيد التشغيل. هل أنت متأكد أنك تريد الخروج؟" ) self.YES = "نعم" self.NO = "لا" self.COMPLETED = "مكتمل" # أنواع الملفات self.ALL_FILES = "جميع الملفات (*)" self.GGUF_FILES = "ملفات GGUF (*.gguf)" self.DAT_FILES = "ملفات DAT (*.dat)" self.JSON_FILES = "ملفات JSON (*.json)" self.BIN_FILES = "ملفات ثنائية (*.bin)" self.LORA_FILES = "ملفات LoRA (*.bin *.gguf)" self.GGUF_AND_BIN_FILES = "ملفات GGUF وثنائية (*.gguf *.bin)" self.SHARDED = "مجزأ" # رسائل الحالة self.DOWNLOAD_COMPLETE = "اكتمل التنزيل" self.CUDA_EXTRACTION_FAILED = "فشل استخراج CUDA" self.PRESET_SAVED = "تم حفظ الإعداد المسبق" self.PRESET_LOADED = "تم تحميل الإعداد المسبق" self.NO_ASSET_SELECTED = "لم يتم اختيار أي أصل" self.DOWNLOAD_FAILED = "فشل التنزيل" self.NO_BACKEND_SELECTED = "لم يتم اختيار أي خلفية" self.NO_MODEL_SELECTED = "لم يتم اختيار أي نموذج" self.NO_SUITABLE_CUDA_BACKENDS = "لم يتم العثور على خلفيات CUDA مناسبة" self.IN_PROGRESS = "قيد التنفيذ" self.LLAMACPP_DOWNLOADED_EXTRACTED = "تم تنزيل واستخراج ثنائي llama.cpp إلى {0}" self.CUDA_FILES_EXTRACTED = "تم استخراج ملفات CUDA إلى" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "لم يتم العثور على خلفية CUDA مناسبة للاستخراج" ) self.ERROR_FETCHING_RELEASES = "خطأ في جلب الإصدارات: {0}" self.CONFIRM_DELETION_TITLE = "تأكيد الحذف" self.LOG_FOR = "سجل لـ {0}" self.FAILED_TO_LOAD_PRESET = "فشل تحميل الإعداد المسبق: {0}" self.INITIALIZING_AUTOGGUF = "جاري تهيئة تطبيق AutoGGUF" self.AUTOGGUF_INITIALIZATION_COMPLETE = "اكتملت تهيئة AutoGGUF" self.REFRESHING_BACKENDS = "جاري تحديث الخلفيات" self.NO_BACKENDS_AVAILABLE = "لا توجد خلفيات متاحة" self.FOUND_VALID_BACKENDS = "تم العثور على {0} خلفيات صالحة" self.SAVING_PRESET = "جاري حفظ الإعداد المسبق" self.PRESET_SAVED_TO = "تم حفظ الإعداد المسبق في {0}" self.LOADING_PRESET = "جاري تحميل الإعداد المسبق" self.PRESET_LOADED_FROM = "تم تحميل الإعداد المسبق من {0}" self.ADDING_KV_OVERRIDE = "إضافة تجاوز KV: {0}" self.SAVING_TASK_PRESET = "جاري حفظ إعداد مسبق للمهمة {0}" self.TASK_PRESET_SAVED = "تم حفظ الإعداد المسبق للمهمة" self.TASK_PRESET_SAVED_TO = "تم حفظ الإعداد المسبق للمهمة في {0}" self.RESTARTING_TASK = "إعادة تشغيل المهمة: {0}" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "اكتمل التنزيل. تم الاستخراج إلى: {0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = ( "تم تنزيل واستخراج ثنائي llama.cpp إلى {0}" ) self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "لم يتم العثور على خلفية CUDA مناسبة للاستخراج" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "تم تنزيل واستخراج ثنائي llama.cpp إلى {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "جاري تحديث إصدارات llama.cpp" self.UPDATING_ASSET_LIST = "جاري تحديث قائمة الأصول" self.UPDATING_CUDA_OPTIONS = "جاري تحديث خيارات CUDA" self.STARTING_LLAMACPP_DOWNLOAD = "بدء تنزيل llama.cpp" self.UPDATING_CUDA_BACKENDS = "جاري تحديث خلفيات CUDA" self.NO_CUDA_BACKEND_SELECTED = "لم يتم اختيار خلفية CUDA للاستخراج" self.EXTRACTING_CUDA_FILES = "جاري استخراج ملفات CUDA من {0} إلى {1}" self.DOWNLOAD_ERROR = "خطأ في التنزيل: {0}" self.SHOWING_TASK_CONTEXT_MENU = "عرض قائمة سياق المهمة" self.SHOWING_PROPERTIES_FOR_TASK = "عرض خصائص المهمة: {0}" self.CANCELLING_TASK = "إلغاء المهمة: {0}" self.CANCELED = "تم الإلغاء" self.DELETING_TASK = "حذف المهمة: {0}" self.LOADING_MODELS = "جاري تحميل النماذج" self.LOADED_MODELS = "تم تحميل {0} نماذج" self.BROWSING_FOR_MODELS_DIRECTORY = "تصفح مجلد النماذج" self.SELECT_MODELS_DIRECTORY = "اختر مجلد النماذج" self.BROWSING_FOR_OUTPUT_DIRECTORY = "تصفح مجلد الإخراج" self.SELECT_OUTPUT_DIRECTORY = "اختر مجلد الإخراج" self.BROWSING_FOR_LOGS_DIRECTORY = "تصفح مجلد السجلات" self.SELECT_LOGS_DIRECTORY = "اختر مجلد السجلات" self.BROWSING_FOR_IMATRIX_FILE = "تصفح ملف مصفوفة الأهمية" self.SELECT_IMATRIX_FILE = "اختر ملف مصفوفة الأهمية" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} ميجابايت / {2} ميجابايت)" self.CPU_USAGE_FORMAT = "استخدام المعالج: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "التحقق من صحة مدخلات التكميم" self.MODELS_PATH_REQUIRED = "مسار النماذج مطلوب" self.OUTPUT_PATH_REQUIRED = "مسار الإخراج مطلوب" self.LOGS_PATH_REQUIRED = "مسار السجلات مطلوب" self.STARTING_MODEL_QUANTIZATION = "بدء تكميم النموذج" self.INPUT_FILE_NOT_EXIST = "ملف الإدخال '{0}' غير موجود." self.QUANTIZING_MODEL_TO = "تكميم {0} إلى {1}" self.QUANTIZATION_TASK_STARTED = "بدأت مهمة تكميم {0}" self.ERROR_STARTING_QUANTIZATION = "خطأ في بدء التكميم: {0}" self.UPDATING_MODEL_INFO = "تحديث معلومات النموذج: {0}" self.TASK_FINISHED = "انتهت المهمة: {0}" self.SHOWING_TASK_DETAILS_FOR = "عرض تفاصيل المهمة لـ: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "تصفح ملف بيانات مصفوفة الأهمية" self.SELECT_DATA_FILE = "اختر ملف البيانات" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "تصفح ملف نموذج مصفوفة الأهمية" self.SELECT_MODEL_FILE = "اختر ملف النموذج" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "تصفح ملف إخراج مصفوفة الأهمية" self.SELECT_OUTPUT_FILE = "اختر ملف الإخراج" self.STARTING_IMATRIX_GENERATION = "بدء توليد مصفوفة الأهمية" self.BACKEND_PATH_NOT_EXIST = "مسار الخلفية غير موجود: {0}" self.GENERATING_IMATRIX = "جاري توليد مصفوفة الأهمية" self.ERROR_STARTING_IMATRIX_GENERATION = "خطأ في بدء توليد مصفوفة الأهمية: {0}" self.IMATRIX_GENERATION_TASK_STARTED = "بدأت مهمة توليد مصفوفة الأهمية" self.ERROR_MESSAGE = "خطأ: {0}" self.TASK_ERROR = "خطأ في المهمة: {0}" self.APPLICATION_CLOSING = "جاري إغلاق التطبيق" self.APPLICATION_CLOSED = "تم إغلاق التطبيق" self.SELECT_QUANTIZATION_TYPE = "اختر نوع التكميم" self.ALLOWS_REQUANTIZING = "يسمح بإعادة تكميم التنسورات التي تم تكميمها بالفعل" self.LEAVE_OUTPUT_WEIGHT = "سيترك output.weight بدون (إعادة) تكميم" self.DISABLE_K_QUANT_MIXTURES = ( "تعطيل خلطات k-quant وتكميم جميع التنسورات إلى نفس النوع" ) self.USE_DATA_AS_IMPORTANCE_MATRIX = ( "استخدام البيانات في الملف كمصفوفة أهمية لتحسينات التكميم" ) self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = "استخدام مصفوفة الأهمية لهذه التنسورات" self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "عدم استخدام مصفوفة الأهمية لهذه التنسورات" ) self.OUTPUT_TENSOR_TYPE = "نوع تنسور الإخراج:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = "استخدام هذا النوع لتنسور output.weight" self.TOKEN_EMBEDDING_TYPE = "نوع تضمين الرمز:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "استخدام هذا النوع لتنسور تضمينات الرموز" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "سيولد النموذج المكمم في نفس الأجزاء كالإدخال" ) self.OVERRIDE_MODEL_METADATA = "تجاوز بيانات تعريف النموذج" self.INPUT_DATA_FILE_FOR_IMATRIX = "ملف بيانات الإدخال لتوليد مصفوفة الأهمية" self.MODEL_TO_BE_QUANTIZED = "النموذج المراد تكميمه" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = "مسار الإخراج لمصفوفة الأهمية المولدة" self.HOW_OFTEN_TO_SAVE_IMATRIX = "عدد مرات حفظ مصفوفة الأهمية" self.SET_GPU_OFFLOAD_VALUE = "تعيين قيمة تحميل وحدة معالجة الرسومات (-ngl)" self.STARTING_LORA_CONVERSION = "بدء تحويل LoRA" self.LORA_INPUT_PATH_REQUIRED = "مسار إدخال LoRA مطلوب." self.LORA_OUTPUT_PATH_REQUIRED = "مسار إخراج LoRA مطلوب." self.ERROR_STARTING_LORA_CONVERSION = "خطأ في بدء تحويل LoRA: {}" self.LORA_CONVERSION_TASK_STARTED = "بدأت مهمة تحويل LoRA." self.BROWSING_FOR_LORA_INPUT_DIRECTORY = "تصفح مجلد إدخال LoRA..." self.BROWSING_FOR_LORA_OUTPUT_FILE = "تصفح ملف إخراج LoRA..." self.CONVERTING_LORA = "تحويل LoRA" self.LORA_CONVERSION_FINISHED = "اكتمل تحويل LoRA." self.LORA_FILE_MOVED = "تم نقل ملف LoRA من {} إلى {}." self.LORA_FILE_NOT_FOUND = "لم يتم العثور على ملف LoRA: {}." self.ERROR_MOVING_LORA_FILE = "خطأ في نقل ملف LoRA: {}" self.MODEL_PATH_REQUIRED = "مسار النموذج مطلوب." self.AT_LEAST_ONE_LORA_ADAPTER_REQUIRED = "مطلوب محول LoRA واحد على الأقل." self.INVALID_LORA_SCALE_VALUE = "قيمة مقياس LoRA غير صالحة." self.ERROR_STARTING_LORA_EXPORT = "خطأ في بدء تصدير LoRA: {}" self.LORA_EXPORT_TASK_STARTED = "بدأت مهمة تصدير LoRA." self.EXPORTING_LORA = "جاري تصدير LoRA..." self.BROWSING_FOR_EXPORT_LORA_MODEL_FILE = "تصفح ملف نموذج تصدير LoRA..." self.BROWSING_FOR_EXPORT_LORA_OUTPUT_FILE = "تصفح ملف إخراج تصدير LoRA..." self.ADDING_LORA_ADAPTER = "إضافة محول LoRA..." self.DELETING_LORA_ADAPTER = "حذف محول LoRA..." self.SELECT_LORA_ADAPTER_FILE = "اختر ملف محول LoRA" self.STARTING_LORA_EXPORT = "بدء تصدير LoRA..." self.SELECT_OUTPUT_TYPE = "اختر نوع الإخراج (GGUF أو GGML)" self.BASE_MODEL = "النموذج الأساسي" self.SELECT_BASE_MODEL_FILE = "اختر ملف النموذج الأساسي (GGUF)" self.BASE_MODEL_PATH_REQUIRED = "مسار النموذج الأساسي مطلوب لإخراج GGUF." self.BROWSING_FOR_BASE_MODEL_FILE = "تصفح ملف النموذج الأساسي..." self.SELECT_BASE_MODEL_FOLDER = ( "اختر مجلد النموذج الأساسي (يحتوي على safetensors)" ) self.BROWSING_FOR_BASE_MODEL_FOLDER = "تصفح مجلد النموذج الأساسي..." self.LORA_CONVERSION_FROM_TO = "تحويل LoRA من {} إلى {}" self.GENERATING_IMATRIX_FOR = "توليد مصفوفة الأهمية لـ {}" self.MODEL_PATH_REQUIRED_FOR_IMATRIX = ( "مسار النموذج مطلوب لتوليد مصفوفة الأهمية." ) self.NO_ASSET_SELECTED_FOR_CUDA_CHECK = "لم يتم اختيار أي أصل للتحقق من CUDA" self.NO_QUANTIZATION_TYPE_SELECTED = ( "لم يتم اختيار نوع تكميم. يرجى اختيار نوع تكميم واحد على الأقل." ) self.STARTING_HF_TO_GGUF_CONVERSION = "بدء تحويل HuggingFace إلى GGUF" self.MODEL_DIRECTORY_REQUIRED = "مجلد النموذج مطلوب" self.HF_TO_GGUF_CONVERSION_COMMAND = "أمر تحويل HF إلى GGUF: {}" self.CONVERTING_TO_GGUF = "تحويل {} إلى GGUF" self.ERROR_STARTING_HF_TO_GGUF_CONVERSION = ( "خطأ في بدء تحويل HuggingFace إلى GGUF: {}" ) self.HF_TO_GGUF_CONVERSION_TASK_STARTED = "بدأت مهمة تحويل HuggingFace إلى GGUF" class _Korean(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (자동 GGUF 모델 양자화기)" self.RAM_USAGE = "RAM 사용량:" self.CPU_USAGE = "CPU 사용량:" self.BACKEND = "Llama.cpp 백엔드:" self.REFRESH_BACKENDS = "백엔드 새로 고침" self.MODELS_PATH = "모델 경로:" self.OUTPUT_PATH = "출력 경로:" self.LOGS_PATH = "로그 경로:" self.BROWSE = "찾아보기" self.AVAILABLE_MODELS = "사용 가능한 모델:" self.QUANTIZATION_TYPE = "양자화 유형:" self.ALLOW_REQUANTIZE = "재양자화 허용" self.LEAVE_OUTPUT_TENSOR = "출력 텐서 유지" self.PURE = "순수" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "가중치 포함:" self.EXCLUDE_WEIGHTS = "가중치 제외:" self.USE_OUTPUT_TENSOR_TYPE = "출력 텐서 유형 사용" self.USE_TOKEN_EMBEDDING_TYPE = "토큰 임베딩 유형 사용" self.KEEP_SPLIT = "분할 유지" self.KV_OVERRIDES = "KV 재정의:" self.ADD_NEW_OVERRIDE = "새 재정의 추가" self.QUANTIZE_MODEL = "모델 양자화" self.SAVE_PRESET = "프리셋 저장" self.LOAD_PRESET = "프리셋 로드" self.TASKS = "작업:" self.DOWNLOAD_LLAMACPP = "llama.cpp 다운로드" self.SELECT_RELEASE = "릴리스 선택:" self.SELECT_ASSET = "자산 선택:" self.EXTRACT_CUDA_FILES = "CUDA 파일 추출" self.SELECT_CUDA_BACKEND = "CUDA 백엔드 선택:" self.DOWNLOAD = "다운로드" self.IMATRIX_GENERATION = "IMatrix 생성" self.DATA_FILE = "데이터 파일:" self.MODEL = "모델:" self.OUTPUT = "출력:" self.OUTPUT_FREQUENCY = "출력 빈도:" self.GPU_OFFLOAD = "GPU 오프로드:" self.AUTO = "자동" self.GENERATE_IMATRIX = "IMatrix 생성" self.ERROR = "오류" self.WARNING = "경고" self.PROPERTIES = "속성" self.CANCEL = "취소" self.RESTART = "다시 시작" self.DELETE = "삭제" self.CONFIRM_DELETION = "이 작업을 삭제하시겠습니까?" self.TASK_RUNNING_WARNING = "일부 작업이 아직 실행 중입니다. 종료하시겠습니까?" self.YES = "예" self.NO = "아니요" self.DOWNLOAD_COMPLETE = "다운로드 완료" self.CUDA_EXTRACTION_FAILED = "CUDA 추출 실패" self.PRESET_SAVED = "프리셋 저장됨" self.PRESET_LOADED = "프리셋 로드됨" self.NO_ASSET_SELECTED = "자산이 선택되지 않았습니다" self.DOWNLOAD_FAILED = "다운로드 실패" self.NO_BACKEND_SELECTED = "백엔드가 선택되지 않았습니다" self.NO_MODEL_SELECTED = "모델이 선택되지 않았습니다" self.REFRESH_RELEASES = "릴리스 새로 고침" self.NO_SUITABLE_CUDA_BACKENDS = "적합한 CUDA 백엔드를 찾을 수 없습니다" self.LLAMACPP_DOWNLOADED_EXTRACTED = "llama.cpp 바이너리가 다운로드되어 {0}에 추출되었습니다.\nCUDA 파일이 {1}에 추출되었습니다." self.CUDA_FILES_EXTRACTED = "CUDA 파일이 에 추출되었습니다." self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "추출에 적합한 CUDA 백엔드를 찾을 수 없습니다." ) self.ERROR_FETCHING_RELEASES = "릴리스를 가져오는 중 오류가 발생했습니다: {0}" self.CONFIRM_DELETION_TITLE = "삭제 확인" self.LOG_FOR = "{0}에 대한 로그" self.ALL_FILES = "모든 파일 (*)" self.GGUF_FILES = "GGUF 파일 (*.gguf)" self.DAT_FILES = "DAT 파일 (*.dat)" self.JSON_FILES = "JSON 파일 (*.json)" self.FAILED_LOAD_PRESET = "프리셋을 로드하지 못했습니다: {0}" self.INITIALIZING_AUTOGGUF = "AutoGGUF 애플리케이션을 초기화하는 중입니다." self.AUTOGGUF_INITIALIZATION_COMPLETE = "AutoGGUF 초기화가 완료되었습니다." self.REFRESHING_BACKENDS = "백엔드를 새로 고치는 중입니다." self.NO_BACKENDS_AVAILABLE = "사용 가능한 백엔드가 없습니다." self.FOUND_VALID_BACKENDS = "{0}개의 유효한 백엔드를 찾았습니다." self.SAVING_PRESET = "프리셋을 저장하는 중입니다." self.PRESET_SAVED_TO = "프리셋이 {0}에 저장되었습니다." self.LOADING_PRESET = "프리셋을 로드하는 중입니다." self.PRESET_LOADED_FROM = "{0}에서 프리셋을 로드했습니다." self.ADDING_KV_OVERRIDE = "KV 재정의를 추가하는 중입니다: {0}" self.SAVING_TASK_PRESET = "{0}에 대한 작업 프리셋을 저장하는 중입니다." self.TASK_PRESET_SAVED = "작업 프리셋이 저장되었습니다." self.TASK_PRESET_SAVED_TO = "작업 프리셋이 {0}에 저장되었습니다." self.RESTARTING_TASK = "작업을 다시 시작하는 중입니다: {0}" self.IN_PROGRESS = "진행 중" self.DOWNLOAD_FINISHED_EXTRACTED_TO = ( "다운로드가 완료되었습니다. 추출 위치: {0}" ) self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "llama.cpp 바이너리가 다운로드되어 {0}에 추출되었습니다.\nCUDA 파일이 {1}에 추출되었습니다." self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "추출에 적합한 CUDA 백엔드를 찾을 수 없습니다." ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "llama.cpp 바이너리가 다운로드되어 {0}에 추출되었습니다." ) self.REFRESHING_LLAMACPP_RELEASES = "llama.cpp 릴리스를 새로 고치는 중입니다." self.UPDATING_ASSET_LIST = "자산 목록을 업데이트하는 중입니다." self.UPDATING_CUDA_OPTIONS = "CUDA 옵션을 업데이트하는 중입니다." self.STARTING_LLAMACPP_DOWNLOAD = "llama.cpp 다운로드를 시작하는 중입니다." self.UPDATING_CUDA_BACKENDS = "CUDA 백엔드를 업데이트하는 중입니다." self.NO_CUDA_BACKEND_SELECTED = "추출에 CUDA 백엔드가 선택되지 않았습니다." self.EXTRACTING_CUDA_FILES = "{0}에서 {1}로 CUDA 파일을 추출하는 중입니다." self.DOWNLOAD_ERROR = "다운로드 오류: {0}" self.SHOWING_TASK_CONTEXT_MENU = "작업 컨텍스트 메뉴를 표시하는 중입니다." self.SHOWING_PROPERTIES_FOR_TASK = "작업에 대한 속성을 표시하는 중입니다: {0}" self.CANCELLING_TASK = "작업을 취소하는 중입니다: {0}" self.CANCELED = "취소됨" self.DELETING_TASK = "작업을 삭제하는 중입니다: {0}" self.LOADING_MODELS = "모델을 로드하는 중입니다." self.LOADED_MODELS = "{0}개의 모델이 로드되었습니다." self.BROWSING_FOR_MODELS_DIRECTORY = "모델 디렉토리를 찾아보는 중입니다." self.SELECT_MODELS_DIRECTORY = "모델 디렉토리 선택" self.BROWSING_FOR_OUTPUT_DIRECTORY = "출력 디렉토리를 찾아보는 중입니다." self.SELECT_OUTPUT_DIRECTORY = "출력 디렉토리 선택" self.BROWSING_FOR_LOGS_DIRECTORY = "로그 디렉토리를 찾아보는 중입니다." self.SELECT_LOGS_DIRECTORY = "로그 디렉토리 선택" self.BROWSING_FOR_IMATRIX_FILE = "IMatrix 파일을 찾아보는 중입니다." self.SELECT_IMATRIX_FILE = "IMatrix 파일 선택" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "CPU 사용량: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "양자화 입력을 검증하는 중입니다." self.MODELS_PATH_REQUIRED = "모델 경로가 필요합니다." self.OUTPUT_PATH_REQUIRED = "출력 경로가 필요합니다." self.LOGS_PATH_REQUIRED = "로그 경로가 필요합니다." self.STARTING_MODEL_QUANTIZATION = "모델 양자화를 시작하는 중입니다." self.INPUT_FILE_NOT_EXIST = "입력 파일 '{0}'이 존재하지 않습니다." self.QUANTIZING_MODEL_TO = "{0}을 {1}(으)로 양자화하는 중입니다." self.QUANTIZATION_TASK_STARTED = "{0}에 대한 양자화 작업이 시작되었습니다." self.ERROR_STARTING_QUANTIZATION = ( "양자화를 시작하는 중 오류가 발생했습니다: {0}" ) self.UPDATING_MODEL_INFO = "모델 정보를 업데이트하는 중입니다: {0}" self.TASK_FINISHED = "작업이 완료되었습니다: {0}" self.SHOWING_TASK_DETAILS_FOR = ( "다음에 대한 작업 세부 정보를 표시하는 중입니다: {0}" ) self.BROWSING_FOR_IMATRIX_DATA_FILE = "IMatrix 데이터 파일을 찾아보는 중입니다." self.SELECT_DATA_FILE = "데이터 파일 선택" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "IMatrix 모델 파일을 찾아보는 중입니다." self.SELECT_MODEL_FILE = "모델 파일 선택" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "IMatrix 출력 파일을 찾아보는 중입니다." self.SELECT_OUTPUT_FILE = "출력 파일 선택" self.STARTING_IMATRIX_GENERATION = "IMatrix 생성을 시작하는 중입니다." self.BACKEND_PATH_NOT_EXIST = "백엔드 경로가 존재하지 않습니다: {0}" self.GENERATING_IMATRIX = "IMatrix를 생성하는 중입니다." self.ERROR_STARTING_IMATRIX_GENERATION = ( "IMatrix 생성을 시작하는 중 오류가 발생했습니다: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "IMatrix 생성 작업이 시작되었습니다." self.ERROR_MESSAGE = "오류: {0}" self.TASK_ERROR = "작업 오류: {0}" self.APPLICATION_CLOSING = "애플리케이션을 닫는 중입니다." self.APPLICATION_CLOSED = "애플리케이션이 닫혔습니다." self.SELECT_QUANTIZATION_TYPE = "양자화 유형을 선택하세요." self.ALLOWS_REQUANTIZING = "이미 양자화된 텐서의 재양자화를 허용합니다." self.LEAVE_OUTPUT_WEIGHT = "output.weight를 (재)양자화하지 않은 상태로 둡니다." self.DISABLE_K_QUANT_MIXTURES = ( "k-양자 혼합을 비활성화하고 모든 텐서를 동일한 유형으로 양자화합니다." ) self.USE_DATA_AS_IMPORTANCE_MATRIX = ( "양자 최적화를 위한 중요도 행렬로 파일의 데이터를 사용합니다." ) self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "이러한 텐서에 중요도 행렬을 사용합니다." ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "이러한 텐서에 중요도 행렬을 사용하지 않습니다." ) self.OUTPUT_TENSOR_TYPE = "출력 텐서 유형:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "output.weight 텐서에 이 유형을 사용합니다." ) self.TOKEN_EMBEDDING_TYPE = "토큰 임베딩 유형:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "토큰 임베딩 텐서에 이 유형을 사용합니다." ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "입력과 동일한 샤드에 양자화된 모델을 생성합니다." ) self.OVERRIDE_MODEL_METADATA = "모델 메타데이터를 재정의합니다." self.INPUT_DATA_FILE_FOR_IMATRIX = "IMatrix 생성을 위한 입력 데이터 파일" self.MODEL_TO_BE_QUANTIZED = "양자화될 모델" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = "생성된 IMatrix의 출력 경로" self.HOW_OFTEN_TO_SAVE_IMATRIX = "IMatrix를 저장할 빈도" self.SET_GPU_OFFLOAD_VALUE = "GPU 오프로드 값 설정 (-ngl)" self.COMPLETED = "완료됨" self.REFRESH_MODELS = "모델 새로고침" class _Italian(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (Quantizzatore Automatico di Modelli GGUF)" self.RAM_USAGE = "Utilizzo RAM:" self.CPU_USAGE = "Utilizzo CPU:" self.BACKEND = "Backend Llama.cpp:" self.REFRESH_BACKENDS = "Aggiorna Backend" self.MODELS_PATH = "Percorso Modelli:" self.OUTPUT_PATH = "Percorso Output:" self.LOGS_PATH = "Percorso Log:" self.BROWSE = "Sfoglia" self.AVAILABLE_MODELS = "Modelli Disponibili:" self.QUANTIZATION_TYPE = "Tipo di Quantizzazione:" self.ALLOW_REQUANTIZE = "Consenti Riquantizzazione" self.LEAVE_OUTPUT_TENSOR = "Lascia Tensore di Output" self.PURE = "Puro" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "Includi Pesi:" self.EXCLUDE_WEIGHTS = "Escludi Pesi:" self.USE_OUTPUT_TENSOR_TYPE = "Usa Tipo di Tensore di Output" self.USE_TOKEN_EMBEDDING_TYPE = "Usa Tipo di Incorporamento Token" self.KEEP_SPLIT = "Mantieni Divisione" self.KV_OVERRIDES = "Override KV:" self.ADD_NEW_OVERRIDE = "Aggiungi Nuovo Override" self.QUANTIZE_MODEL = "Quantizza Modello" self.SAVE_PRESET = "Salva Preimpostazione" self.LOAD_PRESET = "Carica Preimpostazione" self.TASKS = "Attività:" self.DOWNLOAD_LLAMACPP = "Scarica llama.cpp" self.SELECT_RELEASE = "Seleziona Versione:" self.SELECT_ASSET = "Seleziona Asset:" self.EXTRACT_CUDA_FILES = "Estrai File CUDA" self.SELECT_CUDA_BACKEND = "Seleziona Backend CUDA:" self.DOWNLOAD = "Scarica" self.IMATRIX_GENERATION = "Generazione IMatrix" self.DATA_FILE = "File Dati:" self.MODEL = "Modello:" self.OUTPUT = "Output:" self.OUTPUT_FREQUENCY = "Frequenza di Output:" self.GPU_OFFLOAD = "Offload GPU:" self.AUTO = "Auto" self.GENERATE_IMATRIX = "Genera IMatrix" self.ERROR = "Errore" self.WARNING = "Avviso" self.PROPERTIES = "Proprietà" self.CANCEL = "Annulla" self.RESTART = "Riavvia" self.DELETE = "Elimina" self.CONFIRM_DELETION = "Sei sicuro di voler eliminare questa attività?" self.TASK_RUNNING_WARNING = ( "Alcune attività sono ancora in esecuzione. Sei sicuro di voler uscire?" ) self.YES = "Sì" self.NO = "No" self.DOWNLOAD_COMPLETE = "Download Completato" self.CUDA_EXTRACTION_FAILED = "Estrazione CUDA Fallita" self.PRESET_SAVED = "Preimpostazione Salvata" self.PRESET_LOADED = "Preimpostazione Caricata" self.NO_ASSET_SELECTED = "Nessun asset selezionato" self.DOWNLOAD_FAILED = "Download fallito" self.NO_BACKEND_SELECTED = "Nessun backend selezionato" self.NO_MODEL_SELECTED = "Nessun modello selezionato" self.REFRESH_RELEASES = "Aggiorna Versioni" self.NO_SUITABLE_CUDA_BACKENDS = "Nessun backend CUDA adatto trovato" self.LLAMACPP_DOWNLOADED_EXTRACTED = ( "Binario llama.cpp scaricato ed estratto in {0}\nFile CUDA estratti in {1}" ) self.CUDA_FILES_EXTRACTED = "File CUDA estratti in" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "Nessun backend CUDA adatto trovato per l'estrazione" ) self.ERROR_FETCHING_RELEASES = "Errore durante il recupero delle versioni: {0}" self.CONFIRM_DELETION_TITLE = "Conferma Eliminazione" self.LOG_FOR = "Log per {0}" self.ALL_FILES = "Tutti i File (*)" self.GGUF_FILES = "File GGUF (*.gguf)" self.DAT_FILES = "File DAT (*.dat)" self.JSON_FILES = "File JSON (*.json)" self.FAILED_LOAD_PRESET = "Impossibile caricare la preimpostazione: {0}" self.INITIALIZING_AUTOGGUF = "Inizializzazione dell'applicazione AutoGGUF" self.AUTOGGUF_INITIALIZATION_COMPLETE = ( "Inizializzazione di AutoGGUF completata" ) self.REFRESHING_BACKENDS = "Aggiornamento backend" self.NO_BACKENDS_AVAILABLE = "Nessun backend disponibile" self.FOUND_VALID_BACKENDS = "Trovati {0} backend validi" self.SAVING_PRESET = "Salvataggio preimpostazione" self.PRESET_SAVED_TO = "Preimpostazione salvata in {0}" self.LOADING_PRESET = "Caricamento preimpostazione" self.PRESET_LOADED_FROM = "Preimpostazione caricata da {0}" self.ADDING_KV_OVERRIDE = "Aggiunta override KV: {0}" self.SAVING_TASK_PRESET = "Salvataggio preimpostazione attività per {0}" self.TASK_PRESET_SAVED = "Preimpostazione Attività Salvata" self.TASK_PRESET_SAVED_TO = "Preimpostazione attività salvata in {0}" self.RESTARTING_TASK = "Riavvio attività: {0}" self.IN_PROGRESS = "In Corso" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "Download completato. Estratto in: {0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = ( "Binario llama.cpp scaricato ed estratto in {0}\nFile CUDA estratti in {1}" ) self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "Nessun backend CUDA adatto trovato per l'estrazione" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "Binario llama.cpp scaricato ed estratto in {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "Aggiornamento versioni di llama.cpp" self.UPDATING_ASSET_LIST = "Aggiornamento elenco asset" self.UPDATING_CUDA_OPTIONS = "Aggiornamento opzioni CUDA" self.STARTING_LLAMACPP_DOWNLOAD = "Avvio download di llama.cpp" self.UPDATING_CUDA_BACKENDS = "Aggiornamento backend CUDA" self.NO_CUDA_BACKEND_SELECTED = ( "Nessun backend CUDA selezionato per l'estrazione" ) self.EXTRACTING_CUDA_FILES = "Estrazione file CUDA da {0} a {1}" self.DOWNLOAD_ERROR = "Errore di download: {0}" self.SHOWING_TASK_CONTEXT_MENU = "Visualizzazione menu contestuale attività" self.SHOWING_PROPERTIES_FOR_TASK = ( "Visualizzazione proprietà per l'attività: {0}" ) self.CANCELLING_TASK = "Annullamento attività: {0}" self.CANCELED = "Annullato" self.DELETING_TASK = "Eliminazione attività: {0}" self.LOADING_MODELS = "Caricamento modelli" self.LOADED_MODELS = "{0} modelli caricati" self.BROWSING_FOR_MODELS_DIRECTORY = "Esplorazione directory modelli" self.SELECT_MODELS_DIRECTORY = "Seleziona Directory Modelli" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Esplorazione directory output" self.SELECT_OUTPUT_DIRECTORY = "Seleziona Directory Output" self.BROWSING_FOR_LOGS_DIRECTORY = "Esplorazione directory log" self.SELECT_LOGS_DIRECTORY = "Seleziona Directory Log" self.BROWSING_FOR_IMATRIX_FILE = "Esplorazione file IMatrix" self.SELECT_IMATRIX_FILE = "Seleziona File IMatrix" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "Utilizzo CPU: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "Convalida input di quantizzazione" self.MODELS_PATH_REQUIRED = "Il percorso dei modelli è obbligatorio" self.OUTPUT_PATH_REQUIRED = "Il percorso di output è obbligatorio" self.LOGS_PATH_REQUIRED = "Il percorso dei log è obbligatorio" self.STARTING_MODEL_QUANTIZATION = "Avvio quantizzazione del modello" self.INPUT_FILE_NOT_EXIST = "Il file di input '{0}' non esiste." self.QUANTIZING_MODEL_TO = "Quantizzazione di {0} a {1}" self.QUANTIZATION_TASK_STARTED = "Attività di quantizzazione avviata per {0}" self.ERROR_STARTING_QUANTIZATION = ( "Errore durante l'avvio della quantizzazione: {0}" ) self.UPDATING_MODEL_INFO = "Aggiornamento informazioni sul modello: {0}" self.TASK_FINISHED = "Attività completata: {0}" self.SHOWING_TASK_DETAILS_FOR = "Visualizzazione dettagli attività per: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "Esplorazione file dati IMatrix" self.SELECT_DATA_FILE = "Seleziona File Dati" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "Esplorazione file modello IMatrix" self.SELECT_MODEL_FILE = "Seleziona File Modello" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "Esplorazione file output IMatrix" self.SELECT_OUTPUT_FILE = "Seleziona File Output" self.STARTING_IMATRIX_GENERATION = "Avvio generazione IMatrix" self.BACKEND_PATH_NOT_EXIST = "Il percorso del backend non esiste: {0}" self.GENERATING_IMATRIX = "Generazione IMatrix" self.ERROR_STARTING_IMATRIX_GENERATION = ( "Errore durante l'avvio della generazione di IMatrix: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "Attività di generazione IMatrix avviata" self.ERROR_MESSAGE = "Errore: {0}" self.TASK_ERROR = "Errore attività: {0}" self.APPLICATION_CLOSING = "Chiusura applicazione" self.APPLICATION_CLOSED = "Applicazione chiusa" self.SELECT_QUANTIZATION_TYPE = "Seleziona il tipo di quantizzazione" self.ALLOWS_REQUANTIZING = ( "Consente di riquantizzare tensori che sono già stati quantizzati" ) self.LEAVE_OUTPUT_WEIGHT = "Lascerà output.weight non (ri)quantizzato" self.DISABLE_K_QUANT_MIXTURES = ( "Disabilita le miscele k-quant e quantizza tutti i tensori allo stesso tipo" ) self.USE_DATA_AS_IMPORTANCE_MATRIX = "Utilizza i dati nel file come matrice di importanza per le ottimizzazioni di quantizzazione" self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Usa la matrice di importanza per questi tensori" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Non usare la matrice di importanza per questi tensori" ) self.OUTPUT_TENSOR_TYPE = "Tipo di Tensore di Output:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Usa questo tipo per il tensore output.weight" ) self.TOKEN_EMBEDDING_TYPE = "Tipo di Incorporamento Token:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Usa questo tipo per il tensore di incorporamenti token" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "Genererà il modello quantizzato negli stessi frammenti dell'input" ) self.OVERRIDE_MODEL_METADATA = "Sovrascrivi i metadati del modello" self.INPUT_DATA_FILE_FOR_IMATRIX = ( "File di dati di input per la generazione di IMatrix" ) self.MODEL_TO_BE_QUANTIZED = "Modello da quantizzare" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = ( "Percorso di output per l'IMatrix generato" ) self.HOW_OFTEN_TO_SAVE_IMATRIX = "Con quale frequenza salvare l'IMatrix" self.SET_GPU_OFFLOAD_VALUE = "Imposta il valore di offload GPU (-ngl)" self.COMPLETED = "Completato" self.REFRESH_MODELS = "Aggiorna modelli" class _Turkish(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (Otomatik GGUF Modeli Niceleyici)" self.RAM_USAGE = "RAM Kullanımı:" self.CPU_USAGE = "CPU Kullanımı:" self.BACKEND = "Llama.cpp Arka Uç:" self.REFRESH_BACKENDS = "Arka Uçları Yenile" self.MODELS_PATH = "Modeller Yolu:" self.OUTPUT_PATH = "Çıkış Yolu:" self.LOGS_PATH = "Günlükler Yolu:" self.BROWSE = "Gözat" self.AVAILABLE_MODELS = "Kullanılabilir Modeller:" self.QUANTIZATION_TYPE = "Niceleme Türü:" self.ALLOW_REQUANTIZE = "Yeniden Nicelemeye İzin Ver" self.LEAVE_OUTPUT_TENSOR = "Çıkış Tensörünü Bırak" self.PURE = "Saf" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "Ağırlıkları Dahil Et:" self.EXCLUDE_WEIGHTS = "Ağırlıkları Hariç Tut:" self.USE_OUTPUT_TENSOR_TYPE = "Çıkış Tensör Türünü Kullan" self.USE_TOKEN_EMBEDDING_TYPE = "Token Gömme Türünü Kullan" self.KEEP_SPLIT = "Bölmeyi Koru" self.KV_OVERRIDES = "KV Geçersiz Kılmaları:" self.ADD_NEW_OVERRIDE = "Yeni Geçersiz Kılma Ekle" self.QUANTIZE_MODEL = "Modeli Nicele" self.SAVE_PRESET = "Ön Ayarı Kaydet" self.LOAD_PRESET = "Ön Ayarı Yükle" self.TASKS = "Görevler:" self.DOWNLOAD_LLAMACPP = "llama.cpp'yi İndir" self.SELECT_RELEASE = "Sürümü Seç:" self.SELECT_ASSET = "Varlığı Seç:" self.EXTRACT_CUDA_FILES = "CUDA Dosyalarını Çıkar" self.SELECT_CUDA_BACKEND = "CUDA Arka Ucunu Seç:" self.DOWNLOAD = "İndir" self.IMATRIX_GENERATION = "IMatrix Üretimi" self.DATA_FILE = "Veri Dosyası:" self.MODEL = "Model:" self.OUTPUT = "Çıkış:" self.OUTPUT_FREQUENCY = "Çıkış Sıklığı:" self.GPU_OFFLOAD = "GPU Yük Boşaltma:" self.AUTO = "Otomatik" self.GENERATE_IMATRIX = "IMatrix Oluştur" self.ERROR = "Hata" self.WARNING = "Uyarı" self.PROPERTIES = "Özellikler" self.CANCEL = "İptal" self.RESTART = "Yeniden Başlat" self.DELETE = "Sil" self.CONFIRM_DELETION = "Bu görevi silmek istediğinizden emin misiniz?" self.TASK_RUNNING_WARNING = ( "Bazı görevler hala çalışıyor. Çıkmak istediğinizden emin misiniz?" ) self.YES = "Evet" self.NO = "Hayır" self.DOWNLOAD_COMPLETE = "İndirme Tamamlandı" self.CUDA_EXTRACTION_FAILED = "CUDA Çıkarma Başarısız" self.PRESET_SAVED = "Ön Ayar Kaydedildi" self.PRESET_LOADED = "Ön Ayar Yüklendi" self.NO_ASSET_SELECTED = "Varlık seçilmedi" self.DOWNLOAD_FAILED = "İndirme başarısız" self.NO_BACKEND_SELECTED = "Arka uç seçilmedi" self.NO_MODEL_SELECTED = "Model seçilmedi" self.REFRESH_RELEASES = "Sürümleri Yenile" self.NO_SUITABLE_CUDA_BACKENDS = "Uygun CUDA arka uçları bulunamadı" self.LLAMACPP_DOWNLOADED_EXTRACTED = "llama.cpp ikili dosyası indirildi ve {0} konumuna çıkarıldı\nCUDA dosyaları {1} konumuna çıkarıldı" self.CUDA_FILES_EXTRACTED = "CUDA dosyaları konumuna çıkarıldı" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "Çıkarma için uygun bir CUDA arka ucu bulunamadı" ) self.ERROR_FETCHING_RELEASES = "Sürümleri getirirken hata oluştu: {0}" self.CONFIRM_DELETION_TITLE = "Silmeyi Onayla" self.LOG_FOR = "{0} için Günlük" self.ALL_FILES = "Tüm Dosyalar (*)" self.GGUF_FILES = "GGUF Dosyaları (*.gguf)" self.DAT_FILES = "DAT Dosyaları (*.dat)" self.JSON_FILES = "JSON Dosyaları (*.json)" self.FAILED_LOAD_PRESET = "Ön ayarı yükleme başarısız: {0}" self.INITIALIZING_AUTOGGUF = "AutoGGUF uygulaması başlatılıyor" self.AUTOGGUF_INITIALIZATION_COMPLETE = "AutoGGUF başlatması tamamlandı" self.REFRESHING_BACKENDS = "Arka uçlar yenileniyor" self.NO_BACKENDS_AVAILABLE = "Kullanılabilir arka uç yok" self.FOUND_VALID_BACKENDS = "{0} geçerli arka uç bulundu" self.SAVING_PRESET = "Ön ayar kaydediliyor" self.PRESET_SAVED_TO = "Ön ayar {0} konumuna kaydedildi" self.LOADING_PRESET = "Ön ayar yükleniyor" self.PRESET_LOADED_FROM = "Ön ayar {0} konumundan yüklendi" self.ADDING_KV_OVERRIDE = "KV geçersiz kılma ekleniyor: {0}" self.SAVING_TASK_PRESET = "{0} için görev ön ayarı kaydediliyor" self.TASK_PRESET_SAVED = "Görev Ön Ayarı Kaydedildi" self.TASK_PRESET_SAVED_TO = "Görev ön ayarı {0} konumuna kaydedildi" self.RESTARTING_TASK = "Görev yeniden başlatılıyor: {0}" self.IN_PROGRESS = "Devam Ediyor" self.DOWNLOAD_FINISHED_EXTRACTED_TO = ( "İndirme tamamlandı. Şuraya çıkarıldı: {0}" ) self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "llama.cpp ikili dosyası indirildi ve {0} konumuna çıkarıldı\nCUDA dosyaları {1} konumuna çıkarıldı" self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "Çıkarma için uygun bir CUDA arka ucu bulunamadı" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "llama.cpp ikili dosyası indirildi ve {0} konumuna çıkarıldı" ) self.REFRESHING_LLAMACPP_RELEASES = "llama.cpp sürümleri yenileniyor" self.UPDATING_ASSET_LIST = "Varlık listesi güncelleniyor" self.UPDATING_CUDA_OPTIONS = "CUDA seçenekleri güncelleniyor" self.STARTING_LLAMACPP_DOWNLOAD = "llama.cpp indirme başlatılıyor" self.UPDATING_CUDA_BACKENDS = "CUDA arka uçları güncelleniyor" self.NO_CUDA_BACKEND_SELECTED = "Çıkarma için CUDA arka ucu seçilmedi" self.EXTRACTING_CUDA_FILES = ( "CUDA dosyaları {0} konumundan {1} konumuna çıkarılıyor" ) self.DOWNLOAD_ERROR = "İndirme hatası: {0}" self.SHOWING_TASK_CONTEXT_MENU = "Görev bağlam menüsü gösteriliyor" self.SHOWING_PROPERTIES_FOR_TASK = "Görev için özellikler gösteriliyor: {0}" self.CANCELLING_TASK = "Görev iptal ediliyor: {0}" self.CANCELED = "İptal Edildi" self.DELETING_TASK = "Görev siliniyor: {0}" self.LOADING_MODELS = "Modeller yükleniyor" self.LOADED_MODELS = "{0} model yüklendi" self.BROWSING_FOR_MODELS_DIRECTORY = "Modeller dizinine göz atılıyor" self.SELECT_MODELS_DIRECTORY = "Modeller Dizini Seç" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Çıkış dizinine göz atılıyor" self.SELECT_OUTPUT_DIRECTORY = "Çıkış Dizini Seç" self.BROWSING_FOR_LOGS_DIRECTORY = "Günlükler dizinine göz atılıyor" self.SELECT_LOGS_DIRECTORY = "Günlükler Dizini Seç" self.BROWSING_FOR_IMATRIX_FILE = "IMatrix dosyasına göz atılıyor" self.SELECT_IMATRIX_FILE = "IMatrix Dosyası Seç" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "CPU Kullanımı: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "Niceleme girişleri doğrulanıyor" self.MODELS_PATH_REQUIRED = "Modeller yolu gerekli" self.OUTPUT_PATH_REQUIRED = "Çıkış yolu gerekli" self.LOGS_PATH_REQUIRED = "Günlükler yolu gerekli" self.STARTING_MODEL_QUANTIZATION = "Model niceleme başlatılıyor" self.INPUT_FILE_NOT_EXIST = "Giriş dosyası '{0}' mevcut değil." self.QUANTIZING_MODEL_TO = "{0} öğesini {1} öğesine niceleme" self.QUANTIZATION_TASK_STARTED = "{0} için niceleme görevi başlatıldı" self.ERROR_STARTING_QUANTIZATION = "Niceleme başlatılırken hata oluştu: {0}" self.UPDATING_MODEL_INFO = "Model bilgileri güncelleniyor: {0}" self.TASK_FINISHED = "Görev tamamlandı: {0}" self.SHOWING_TASK_DETAILS_FOR = "Şunun için görev ayrıntıları gösteriliyor: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "IMatrix veri dosyasına göz atılıyor" self.SELECT_DATA_FILE = "Veri Dosyası Seç" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "IMatrix model dosyasına göz atılıyor" self.SELECT_MODEL_FILE = "Model Dosyası Seç" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "IMatrix çıkış dosyasına göz atılıyor" self.SELECT_OUTPUT_FILE = "Çıkış Dosyası Seç" self.STARTING_IMATRIX_GENERATION = "IMatrix üretimi başlatılıyor" self.BACKEND_PATH_NOT_EXIST = "Arka uç yolu mevcut değil: {0}" self.GENERATING_IMATRIX = "IMatrix oluşturuluyor" self.ERROR_STARTING_IMATRIX_GENERATION = ( "IMatrix üretimi başlatılırken hata oluştu: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "IMatrix oluşturma görevi başlatıldı" self.ERROR_MESSAGE = "Hata: {0}" self.TASK_ERROR = "Görev hatası: {0}" self.APPLICATION_CLOSING = "Uygulama kapatılıyor" self.APPLICATION_CLOSED = "Uygulama kapatıldı" self.SELECT_QUANTIZATION_TYPE = "Niceleme türünü seçin" self.ALLOWS_REQUANTIZING = ( "Zaten niceleme yapılmış tensörlerin yeniden nicelemesine izin verir" ) self.LEAVE_OUTPUT_WEIGHT = ( "output.weight öğesini (yeniden) nicelememiş halde bırakır" ) self.DISABLE_K_QUANT_MIXTURES = "k-Quant karışımlarını devre dışı bırakın ve tüm tensörleri aynı türe niceleyin" self.USE_DATA_AS_IMPORTANCE_MATRIX = "Quant optimizasyonları için dosyadaki verileri önem matrisi olarak kullanın" self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Bu tensörler için önem matrisini kullanın" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Bu tensörler için önem matrisini kullanmayın" ) self.OUTPUT_TENSOR_TYPE = "Çıkış Tensör Türü:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "output.weight tensörü için bu türü kullanın" ) self.TOKEN_EMBEDDING_TYPE = "Token Gömme Türü:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Token gömme tensörü için bu türü kullanın" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "Nicelemeli modeli girişle aynı parçalarda oluşturacaktır" ) self.OVERRIDE_MODEL_METADATA = "Model meta verilerini geçersiz kıl" self.INPUT_DATA_FILE_FOR_IMATRIX = "IMatrix oluşturma için giriş veri dosyası" self.MODEL_TO_BE_QUANTIZED = "Nicelemeli model" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = "Oluşturulan IMatrix için çıkış yolu" self.HOW_OFTEN_TO_SAVE_IMATRIX = "IMatrix'in ne sıklıkta kaydedileceği" self.SET_GPU_OFFLOAD_VALUE = "GPU yük boşaltma değerini ayarla (-ngl)" self.COMPLETED = "Tamamlandı" self.REFRESH_MODELS = "Modelleri yenile" class _Dutch(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (automatische GGUF-modelkwantisering)" self.RAM_USAGE = "RAM-gebruik:" self.CPU_USAGE = "CPU-gebruik:" self.BACKEND = "Llama.cpp Backend:" self.REFRESH_BACKENDS = "Backends vernieuwen" self.MODELS_PATH = "Modelpad:" self.OUTPUT_PATH = "Uitvoerpad:" self.LOGS_PATH = "Logboekpad:" self.BROWSE = "Bladeren" self.AVAILABLE_MODELS = "Beschikbare modellen:" self.QUANTIZATION_TYPE = "Kwantiseringstype:" self.ALLOW_REQUANTIZE = "Herkwantisering toestaan" self.LEAVE_OUTPUT_TENSOR = "Uitvoertensor behouden" self.PURE = "Zuiver" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "Gewichten opnemen:" self.EXCLUDE_WEIGHTS = "Gewichten uitsluiten:" self.USE_OUTPUT_TENSOR_TYPE = "Uitvoertensortype gebruiken" self.USE_TOKEN_EMBEDDING_TYPE = "Tokeninbeddingstype gebruiken" self.KEEP_SPLIT = "Splitsing behouden" self.KV_OVERRIDES = "KV-overschrijvingen:" self.ADD_NEW_OVERRIDE = "Nieuwe overschrijving toevoegen" self.QUANTIZE_MODEL = "Model kwantiseren" self.SAVE_PRESET = "Voorinstelling opslaan" self.LOAD_PRESET = "Voorinstelling laden" self.TASKS = "Taken:" self.DOWNLOAD_LLAMACPP = "Download llama.cpp" self.SELECT_RELEASE = "Selecteer release:" self.SELECT_ASSET = "Selecteer item:" self.EXTRACT_CUDA_FILES = "CUDA-bestanden uitpakken" self.SELECT_CUDA_BACKEND = "Selecteer CUDA-backend:" self.DOWNLOAD = "Downloaden" self.IMATRIX_GENERATION = "IMatrix-generatie" self.DATA_FILE = "Gegevensbestand:" self.MODEL = "Model:" self.OUTPUT = "Uitvoer:" self.OUTPUT_FREQUENCY = "Uitvoerfrequentie:" self.GPU_OFFLOAD = "GPU-offload:" self.AUTO = "Automatisch" self.GENERATE_IMATRIX = "IMatrix genereren" self.ERROR = "Fout" self.WARNING = "Waarschuwing" self.PROPERTIES = "Eigenschappen" self.CANCEL = "Annuleren" self.RESTART = "Opnieuw starten" self.DELETE = "Verwijderen" self.CONFIRM_DELETION = "Weet u zeker dat u deze taak wilt verwijderen?" self.TASK_RUNNING_WARNING = ( "Sommige taken worden nog uitgevoerd. Weet u zeker dat u wilt afsluiten?" ) self.YES = "Ja" self.NO = "Nee" self.DOWNLOAD_COMPLETE = "Download voltooid" self.CUDA_EXTRACTION_FAILED = "CUDA-extractie mislukt" self.PRESET_SAVED = "Voorinstelling opgeslagen" self.PRESET_LOADED = "Voorinstelling geladen" self.NO_ASSET_SELECTED = "Geen item geselecteerd" self.DOWNLOAD_FAILED = "Download mislukt" self.NO_BACKEND_SELECTED = "Geen backend geselecteerd" self.NO_MODEL_SELECTED = "Geen model geselecteerd" self.REFRESH_RELEASES = "Releases vernieuwen" self.NO_SUITABLE_CUDA_BACKENDS = "Geen geschikte CUDA-backends gevonden" self.LLAMACPP_DOWNLOADED_EXTRACTED = "llama.cpp-binairbestand gedownload en uitgepakt naar {0}\nCUDA-bestanden uitgepakt naar {1}" self.CUDA_FILES_EXTRACTED = "CUDA-bestanden uitgepakt naar" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "Geen geschikte CUDA-backend gevonden voor extractie" ) self.ERROR_FETCHING_RELEASES = "Fout bij het ophalen van releases: {0}" self.CONFIRM_DELETION_TITLE = "Verwijdering bevestigen" self.LOG_FOR = "Logboek voor {0}" self.ALL_FILES = "Alle bestanden (*)" self.GGUF_FILES = "GGUF-bestanden (*.gguf)" self.DAT_FILES = "DAT-bestanden (*.dat)" self.JSON_FILES = "JSON-bestanden (*.json)" self.FAILED_LOAD_PRESET = "Voorinstelling laden mislukt: {0}" self.INITIALIZING_AUTOGGUF = "AutoGGUF-applicatie wordt geïnitialiseerd" self.AUTOGGUF_INITIALIZATION_COMPLETE = "AutoGGUF-initialisatie voltooid" self.REFRESHING_BACKENDS = "Backends worden vernieuwd" self.NO_BACKENDS_AVAILABLE = "Geen backends beschikbaar" self.FOUND_VALID_BACKENDS = "{0} geldige backends gevonden" self.SAVING_PRESET = "Voorinstelling wordt opgeslagen" self.PRESET_SAVED_TO = "Voorinstelling opgeslagen in {0}" self.LOADING_PRESET = "Voorinstelling wordt geladen" self.PRESET_LOADED_FROM = "Voorinstelling geladen van {0}" self.ADDING_KV_OVERRIDE = "KV-overschrijving toevoegen: {0}" self.SAVING_TASK_PRESET = "Taakvoorinstelling opslaan voor {0}" self.TASK_PRESET_SAVED = "Taakvoorinstelling opgeslagen" self.TASK_PRESET_SAVED_TO = "Taakvoorinstelling opgeslagen in {0}" self.RESTARTING_TASK = "Taak opnieuw starten: {0}" self.IN_PROGRESS = "Bezig" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "Download voltooid. Uitgepakt naar: {0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "llama.cpp-binairbestand gedownload en uitgepakt naar {0}\nCUDA-bestanden uitgepakt naar {1}" self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "Geen geschikte CUDA-backend gevonden voor extractie" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "llama.cpp-binairbestand gedownload en uitgepakt naar {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "llama.cpp-releases worden vernieuwd" self.UPDATING_ASSET_LIST = "Itemlijst wordt bijgewerkt" self.UPDATING_CUDA_OPTIONS = "CUDA-opties worden bijgewerkt" self.STARTING_LLAMACPP_DOWNLOAD = "Downloaden van llama.cpp wordt gestart" self.UPDATING_CUDA_BACKENDS = "CUDA-backends worden bijgewerkt" self.NO_CUDA_BACKEND_SELECTED = "Geen CUDA-backend geselecteerd voor extractie" self.EXTRACTING_CUDA_FILES = "CUDA-bestanden uitpakken van {0} naar {1}" self.DOWNLOAD_ERROR = "Downloadfout: {0}" self.SHOWING_TASK_CONTEXT_MENU = "Taakcontextmenu weergeven" self.SHOWING_PROPERTIES_FOR_TASK = "Eigenschappen voor taak weergeven: {0}" self.CANCELLING_TASK = "Taak annuleren: {0}" self.CANCELED = "Geannuleerd" self.DELETING_TASK = "Taak verwijderen: {0}" self.LOADING_MODELS = "Modellen laden" self.LOADED_MODELS = "{0} modellen geladen" self.BROWSING_FOR_MODELS_DIRECTORY = "Bladeren naar modelmap" self.SELECT_MODELS_DIRECTORY = "Selecteer modelmap" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Bladeren naar uitvoermap" self.SELECT_OUTPUT_DIRECTORY = "Selecteer uitvoermap" self.BROWSING_FOR_LOGS_DIRECTORY = "Bladeren naar logboekmap" self.SELECT_LOGS_DIRECTORY = "Selecteer logboekmap" self.BROWSING_FOR_IMATRIX_FILE = "Bladeren naar IMatrix-bestand" self.SELECT_IMATRIX_FILE = "Selecteer IMatrix-bestand" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "CPU-gebruik: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "Kwantiseringsinvoer valideren" self.MODELS_PATH_REQUIRED = "Modelpad is vereist" self.OUTPUT_PATH_REQUIRED = "Uitvoerpad is vereist" self.LOGS_PATH_REQUIRED = "Logboekpad is vereist" self.STARTING_MODEL_QUANTIZATION = "Modelkwantisering starten" self.INPUT_FILE_NOT_EXIST = "Invoerbestand '{0}' bestaat niet." self.QUANTIZING_MODEL_TO = "Kwantiseren van {0} naar {1}" self.QUANTIZATION_TASK_STARTED = "Kwantiseringstaak gestart voor {0}" self.ERROR_STARTING_QUANTIZATION = "Fout bij het starten van kwantisering: {0}" self.UPDATING_MODEL_INFO = "Modelinformatie bijwerken: {0}" self.TASK_FINISHED = "Taak voltooid: {0}" self.SHOWING_TASK_DETAILS_FOR = "Taakdetails weergeven voor: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "Bladeren naar IMatrix-gegevensbestand" self.SELECT_DATA_FILE = "Selecteer gegevensbestand" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "Bladeren naar IMatrix-modelbestand" self.SELECT_MODEL_FILE = "Selecteer modelbestand" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "Bladeren naar IMatrix-uitvoerbestand" self.SELECT_OUTPUT_FILE = "Selecteer uitvoerbestand" self.STARTING_IMATRIX_GENERATION = "IMatrix-generatie starten" self.BACKEND_PATH_NOT_EXIST = "Backendpad bestaat niet: {0}" self.GENERATING_IMATRIX = "IMatrix genereren" self.ERROR_STARTING_IMATRIX_GENERATION = ( "Fout bij het starten van IMatrix-generatie: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "IMatrix-generatietaak gestart" self.ERROR_MESSAGE = "Fout: {0}" self.TASK_ERROR = "Taakfout: {0}" self.APPLICATION_CLOSING = "Applicatie wordt afgesloten" self.APPLICATION_CLOSED = "Applicatie afgesloten" self.SELECT_QUANTIZATION_TYPE = "Selecteer het kwantiseringstype" self.ALLOWS_REQUANTIZING = ( "Staat herkwantisering toe van tensoren die al gekwantiseerd zijn" ) self.LEAVE_OUTPUT_WEIGHT = "Laat output.weight niet (opnieuw) gekwantiseerd" self.DISABLE_K_QUANT_MIXTURES = "Schakel k-kwant-mengsels uit en kwantiseer alle tensoren naar hetzelfde type" self.USE_DATA_AS_IMPORTANCE_MATRIX = "Gebruik gegevens in bestand als belangrijkheidsmatrix voor kwant-optimalisaties" self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Gebruik belangrijkheidsmatrix voor deze tensoren" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Gebruik geen belangrijkheidsmatrix voor deze tensoren" ) self.OUTPUT_TENSOR_TYPE = "Uitvoertensortype:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Gebruik dit type voor de output.weight-tensor" ) self.TOKEN_EMBEDDING_TYPE = "Tokeninbeddingstype:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Gebruik dit type voor de tokeninbeddingstensor" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "Genereert een gekwantiseerd model in dezelfde shards als de invoer" ) self.OVERRIDE_MODEL_METADATA = "Modelmetadata overschrijven" self.INPUT_DATA_FILE_FOR_IMATRIX = ( "Invoergegevensbestand voor IMatrix-generatie" ) self.MODEL_TO_BE_QUANTIZED = "Te kwantiseren model" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = ( "Uitvoerpad voor de gegenereerde IMatrix" ) self.HOW_OFTEN_TO_SAVE_IMATRIX = "Hoe vaak de IMatrix moet worden opgeslagen" self.SET_GPU_OFFLOAD_VALUE = "Stel de GPU-offloadwaarde in (-ngl)" self.COMPLETED = "Voltooid" self.REFRESH_MODELS = "Modellen vernieuwen" class _Finnish(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (automaattinen GGUF-mallien kvantisoija)" self.RAM_USAGE = "RAM-muistin käyttö:" self.CPU_USAGE = "CPU:n käyttö:" self.BACKEND = "Llama.cpp-taustaosa:" self.REFRESH_BACKENDS = "Päivitä taustaosat" self.MODELS_PATH = "Mallien polku:" self.OUTPUT_PATH = "Tulostepolku:" self.LOGS_PATH = "Lokien polku:" self.BROWSE = "Selaa" self.AVAILABLE_MODELS = "Käytettävissä olevat mallit:" self.QUANTIZATION_TYPE = "Kvantisointityyppi:" self.ALLOW_REQUANTIZE = "Salli uudelleenkvantisointi" self.LEAVE_OUTPUT_TENSOR = "Jätä tulostensori" self.PURE = "Puhdas" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "Sisällytä painot:" self.EXCLUDE_WEIGHTS = "Sulje pois painot:" self.USE_OUTPUT_TENSOR_TYPE = "Käytä tulostensorin tyyppiä" self.USE_TOKEN_EMBEDDING_TYPE = "Käytä token-upotustyyppiä" self.KEEP_SPLIT = "Säilytä jako" self.KV_OVERRIDES = "KV-ohitukset:" self.ADD_NEW_OVERRIDE = "Lisää uusi ohitus" self.QUANTIZE_MODEL = "Kvantisoi malli" self.SAVE_PRESET = "Tallenna esiasetus" self.LOAD_PRESET = "Lataa esiasetus" self.TASKS = "Tehtävät:" self.DOWNLOAD_LLAMACPP = "Lataa llama.cpp" self.SELECT_RELEASE = "Valitse julkaisu:" self.SELECT_ASSET = "Valitse resurssi:" self.EXTRACT_CUDA_FILES = "Pura CUDA-tiedostot" self.SELECT_CUDA_BACKEND = "Valitse CUDA-taustaosa:" self.DOWNLOAD = "Lataa" self.IMATRIX_GENERATION = "IMatrix-generointi" self.DATA_FILE = "Datatiedosto:" self.MODEL = "Malli:" self.OUTPUT = "Tuloste:" self.OUTPUT_FREQUENCY = "Tulostetaajuus:" self.GPU_OFFLOAD = "GPU-kuormansiirto:" self.AUTO = "Automaattinen" self.GENERATE_IMATRIX = "Generoi IMatrix" self.ERROR = "Virhe" self.WARNING = "Varoitus" self.PROPERTIES = "Ominaisuudet" self.CANCEL = "Peruuta" self.RESTART = "Käynnistä uudelleen" self.DELETE = "Poista" self.CONFIRM_DELETION = "Haluatko varmasti poistaa tämän tehtävän?" self.TASK_RUNNING_WARNING = ( "Jotkin tehtävät ovat vielä käynnissä. Haluatko varmasti lopettaa?" ) self.YES = "Kyllä" self.NO = "Ei" self.DOWNLOAD_COMPLETE = "Lataus valmis" self.CUDA_EXTRACTION_FAILED = "CUDA-purku epäonnistui" self.PRESET_SAVED = "Esiasetus tallennettu" self.PRESET_LOADED = "Esiasetus ladattu" self.NO_ASSET_SELECTED = "Ei resurssia valittuna" self.DOWNLOAD_FAILED = "Lataus epäonnistui" self.NO_BACKEND_SELECTED = "Ei taustaosaa valittuna" self.NO_MODEL_SELECTED = "Ei mallia valittuna" self.REFRESH_RELEASES = "Päivitä julkaisut" self.NO_SUITABLE_CUDA_BACKENDS = "Sopivia CUDA-taustaosoja ei löytynyt" self.LLAMACPP_DOWNLOADED_EXTRACTED = "llama.cpp-binaaritiedosto ladattu ja purettu kansioon {0}\nCUDA-tiedostot purettu kansioon {1}" self.CUDA_FILES_EXTRACTED = "CUDA-tiedostot purettu kansioon" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "Sopivaa CUDA-taustaosaa purkua varten ei löytynyt" ) self.ERROR_FETCHING_RELEASES = "Virhe haettaessa julkaisuja: {0}" self.CONFIRM_DELETION_TITLE = "Vahvista poisto" self.LOG_FOR = "Loki kohteelle {0}" self.ALL_FILES = "Kaikki tiedostot (*)" self.GGUF_FILES = "GGUF-tiedostot (*.gguf)" self.DAT_FILES = "DAT-tiedostot (*.dat)" self.JSON_FILES = "JSON-tiedostot (*.json)" self.FAILED_LOAD_PRESET = "Esiasetuksen lataus epäonnistui: {0}" self.INITIALIZING_AUTOGGUF = "Alustetaan AutoGGUF-sovellusta" self.AUTOGGUF_INITIALIZATION_COMPLETE = "AutoGGUF-alustus valmis" self.REFRESHING_BACKENDS = "Päivitetään taustaosoja" self.NO_BACKENDS_AVAILABLE = "Ei käytettävissä olevia taustaosoja" self.FOUND_VALID_BACKENDS = "Löydettiin {0} kelvollista taustaosaa" self.SAVING_PRESET = "Tallennetaan esiasetusta" self.PRESET_SAVED_TO = "Esiasetus tallennettu kansioon {0}" self.LOADING_PRESET = "Ladataan esiasetusta" self.PRESET_LOADED_FROM = "Esiasetus ladattu kansiosta {0}" self.ADDING_KV_OVERRIDE = "Lisätään KV-ohitus: {0}" self.SAVING_TASK_PRESET = "Tallennetaan tehtäväesiasetusta kohteelle {0}" self.TASK_PRESET_SAVED = "Tehtäväesiasetus tallennettu" self.TASK_PRESET_SAVED_TO = "Tehtäväesiasetus tallennettu kansioon {0}" self.RESTARTING_TASK = "Käynnistetään tehtävä uudelleen: {0}" self.IN_PROGRESS = "Käynnissä" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "Lataus valmis. Purettu kansioon: {0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "llama.cpp-binaaritiedosto ladattu ja purettu kansioon {0}\nCUDA-tiedostot purettu kansioon {1}" self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "Sopivaa CUDA-taustaosaa purkua varten ei löytynyt" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "llama.cpp-binaaritiedosto ladattu ja purettu kansioon {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "Päivitetään llama.cpp-julkaisuja" self.UPDATING_ASSET_LIST = "Päivitetään resurssilistaa" self.UPDATING_CUDA_OPTIONS = "Päivitetään CUDA-asetuksia" self.STARTING_LLAMACPP_DOWNLOAD = "Aloitetaan llama.cpp:n lataus" self.UPDATING_CUDA_BACKENDS = "Päivitetään CUDA-taustaosoja" self.NO_CUDA_BACKEND_SELECTED = "Ei CUDA-taustaosaa valittuna purkua varten" self.EXTRACTING_CUDA_FILES = ( "Puretaan CUDA-tiedostoja kansiosta {0} kansioon {1}" ) self.DOWNLOAD_ERROR = "Latausvirhe: {0}" self.SHOWING_TASK_CONTEXT_MENU = "Näytetään tehtäväkontekstivalikko" self.SHOWING_PROPERTIES_FOR_TASK = "Näytetään tehtävän ominaisuudet: {0}" self.CANCELLING_TASK = "Peruutetaan tehtävää: {0}" self.CANCELED = "Peruutettu" self.DELETING_TASK = "Poistetaan tehtävää: {0}" self.LOADING_MODELS = "Ladataan malleja" self.LOADED_MODELS = "{0} mallia ladattu" self.BROWSING_FOR_MODELS_DIRECTORY = "Selaillaan mallikansiota" self.SELECT_MODELS_DIRECTORY = "Valitse mallikansio" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Selaillaan tulostekansiota" self.SELECT_OUTPUT_DIRECTORY = "Valitse tulostekansio" self.BROWSING_FOR_LOGS_DIRECTORY = "Selaillaan lokikansiota" self.SELECT_LOGS_DIRECTORY = "Valitse lokikansio" self.BROWSING_FOR_IMATRIX_FILE = "Selaillaan IMatrix-tiedostoa" self.SELECT_IMATRIX_FILE = "Valitse IMatrix-tiedosto" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} Mt / {2} Mt)" self.CPU_USAGE_FORMAT = "CPU:n käyttö: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "Vahvistetaan kvantisointisyötteet" self.MODELS_PATH_REQUIRED = "Mallien polku on pakollinen" self.OUTPUT_PATH_REQUIRED = "Tulostepolku on pakollinen" self.LOGS_PATH_REQUIRED = "Lokien polku on pakollinen" self.STARTING_MODEL_QUANTIZATION = "Aloitetaan mallin kvantisointi" self.INPUT_FILE_NOT_EXIST = "Syötetiedostoa '{0}' ei ole." self.QUANTIZING_MODEL_TO = "Kvantisoidaan mallia {0} muotoon {1}" self.QUANTIZATION_TASK_STARTED = ( "Kvantisointitehtävä käynnistetty kohteelle {0}" ) self.ERROR_STARTING_QUANTIZATION = "Virhe kvantisoinnin käynnistyksessä: {0}" self.UPDATING_MODEL_INFO = "Päivitetään mallitietoja: {0}" self.TASK_FINISHED = "Tehtävä valmis: {0}" self.SHOWING_TASK_DETAILS_FOR = "Näytetään tehtävän tiedot kohteelle: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "Selaillaan IMatrix-datatiedostoa" self.SELECT_DATA_FILE = "Valitse datatiedosto" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "Selaillaan IMatrix-mallitiedostoa" self.SELECT_MODEL_FILE = "Valitse mallitiedosto" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "Selaillaan IMatrix-tulostetiedostoa" self.SELECT_OUTPUT_FILE = "Valitse tulostetiedosto" self.STARTING_IMATRIX_GENERATION = "Aloitetaan IMatrix-generointi" self.BACKEND_PATH_NOT_EXIST = "Taustaosan polkua ei ole: {0}" self.GENERATING_IMATRIX = "Generoidaan IMatrixia" self.ERROR_STARTING_IMATRIX_GENERATION = ( "Virhe IMatrix-generoinnin käynnistyksessä: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "IMatrix-generointi käynnistetty" self.ERROR_MESSAGE = "Virhe: {0}" self.TASK_ERROR = "Tehtävävirhe: {0}" self.APPLICATION_CLOSING = "Sovellus suljetaan" self.APPLICATION_CLOSED = "Sovellus suljettu" self.SELECT_QUANTIZATION_TYPE = "Valitse kvantisointityyppi" self.ALLOWS_REQUANTIZING = ( "Sallii jo kvantisoitujen tensoreiden uudelleenkvantisoinnin" ) self.LEAVE_OUTPUT_WEIGHT = ( "Jättää output.weight-tensorin (uudelleen)kvantisoimatta" ) self.DISABLE_K_QUANT_MIXTURES = "Poista käytöstä k-kvanttisekoitukset ja kvantisoi kaikki tensorit samaan tyyppiin" self.USE_DATA_AS_IMPORTANCE_MATRIX = ( "Käytä tiedoston tietoja kvantisoinnin optimoinnin tärkeysmatriisina" ) self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Käytä tärkeysmatriisia näille tensoreille" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Älä käytä tärkeysmatriisia näille tensoreille" ) self.OUTPUT_TENSOR_TYPE = "Tulostensorin tyyppi:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Käytä tätä tyyppiä output.weight-tensorille" ) self.TOKEN_EMBEDDING_TYPE = "Token-upotustyyppi:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Käytä tätä tyyppiä token-upotustensorille" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "Generoi kvantisoidun mallin samoihin osiin kuin syöte" ) self.OVERRIDE_MODEL_METADATA = "Ohita mallitiedot" self.INPUT_DATA_FILE_FOR_IMATRIX = "IMatrix-generoinnin syötedatatiedosto" self.MODEL_TO_BE_QUANTIZED = "Kvantisoitava malli" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = "Generoidun IMatrixin tulostepolku" self.HOW_OFTEN_TO_SAVE_IMATRIX = "Kuinka usein IMatrix tallennetaan" self.SET_GPU_OFFLOAD_VALUE = "Aseta GPU-kuormansiirron arvo (-ngl)" self.COMPLETED = "Valmis" self.REFRESH_MODELS = "Päivitä mallit" class _Bengali(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (স্বয়ংক্রিয় GGUF মডেল কোয়ান্টাইজার)" self.RAM_USAGE = "RAM ব্যবহার:" self.CPU_USAGE = "CPU ব্যবহার:" self.BACKEND = "Llama.cpp ব্যাকএন্ড:" self.REFRESH_BACKENDS = "ব্যাকএন্ড রিফ্রেশ করুন" self.MODELS_PATH = "মডেল পাথ:" self.OUTPUT_PATH = "আউটপুট পাথ:" self.LOGS_PATH = "লগ পাথ:" self.BROWSE = "ব্রাউজ করুন" self.AVAILABLE_MODELS = "উপলব্ধ মডেল:" self.QUANTIZATION_TYPE = "কোয়ান্টাইজেশন ধরণ:" self.ALLOW_REQUANTIZE = "পুনরায় কোয়ান্টাইজ করার অনুমতি দিন" self.LEAVE_OUTPUT_TENSOR = "আউটপুট টেন্সর রেখে দিন" self.PURE = "বিশুদ্ধ" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "ওজন অন্তর্ভুক্ত করুন:" self.EXCLUDE_WEIGHTS = "ওজন বাদ দিন:" self.USE_OUTPUT_TENSOR_TYPE = "আউটপুট টেন্সর ধরণ ব্যবহার করুন" self.USE_TOKEN_EMBEDDING_TYPE = "টোকেন এম্বেডিং ধরণ ব্যবহার করুন" self.KEEP_SPLIT = "বিভাজন রাখুন" self.KV_OVERRIDES = "KV ওভাররাইড:" self.ADD_NEW_OVERRIDE = "নতুন ওভাররাইড যুক্ত করুন" self.QUANTIZE_MODEL = "মডেল কোয়ান্টাইজ করুন" self.SAVE_PRESET = "প্রিসেট সংরক্ষণ করুন" self.LOAD_PRESET = "প্রিসেট লোড করুন" self.TASKS = "কার্য:" self.DOWNLOAD_LLAMACPP = "llama.cpp ডাউনলোড করুন" self.SELECT_RELEASE = "রিলিজ নির্বাচন করুন:" self.SELECT_ASSET = "অ্যাসেট নির্বাচন করুন:" self.EXTRACT_CUDA_FILES = "CUDA ফাইলগুলি বের করুন" self.SELECT_CUDA_BACKEND = "CUDA ব্যাকএন্ড নির্বাচন করুন:" self.DOWNLOAD = "ডাউনলোড করুন" self.IMATRIX_GENERATION = "IMatrix জেনারেশন" self.DATA_FILE = "ডেটা ফাইল:" self.MODEL = "মডেল:" self.OUTPUT = "আউটপুট:" self.OUTPUT_FREQUENCY = "আউটপুট ফ্রিকোয়েন্সি:" self.GPU_OFFLOAD = "GPU অফলোড:" self.AUTO = "স্বয়ংক্রিয়" self.GENERATE_IMATRIX = "IMatrix তৈরি করুন" self.ERROR = "ত্রুটি" self.WARNING = "সতর্কীকরণ" self.PROPERTIES = "বৈশিষ্ট্য" self.CANCEL = "বাতিল করুন" self.RESTART = "পুনরায় আরম্ভ করুন" self.DELETE = "মুছে ফেলুন" self.CONFIRM_DELETION = "আপনি কি নিশ্চিত যে আপনি এই কাজটি মুছে ফেলতে চান?" self.TASK_RUNNING_WARNING = ( "কিছু কাজ এখনও চলছে। আপনি কি নিশ্চিত যে আপনি প্রস্থান করতে চান?" ) self.YES = "হ্যাঁ" self.NO = "না" self.DOWNLOAD_COMPLETE = "ডাউনলোড সম্পন্ন" self.CUDA_EXTRACTION_FAILED = "CUDA এক্সট্র্যাকশন ব্যর্থ" self.PRESET_SAVED = "প্রিসেট সংরক্ষিত" self.PRESET_LOADED = "প্রিসেট লোড করা হয়েছে" self.NO_ASSET_SELECTED = "কোন অ্যাসেট নির্বাচন করা হয়নি" self.DOWNLOAD_FAILED = "ডাউনলোড ব্যর্থ" self.NO_BACKEND_SELECTED = "কোন ব্যাকএন্ড নির্বাচন করা হয়নি" self.NO_MODEL_SELECTED = "কোন মডেল নির্বাচন করা হয়নি" self.REFRESH_RELEASES = "রিলিজগুলি রিফ্রেশ করুন" self.NO_SUITABLE_CUDA_BACKENDS = "কোন উপযুক্ত CUDA ব্যাকএন্ড পাওয়া যায়নি" self.LLAMACPP_DOWNLOADED_EXTRACTED = "llama.cpp বাইনারি ফাইল ডাউনলোড এবং {0} এ বের করা হয়েছে\nCUDA ফাইলগুলি {1} এ বের করা হয়েছে" self.CUDA_FILES_EXTRACTED = "CUDA ফাইলগুলি তে বের করা হয়েছে" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "এক্সট্র্যাকশনের জন্য কোন উপযুক্ত CUDA ব্যাকএন্ড পাওয়া যায়নি" ) self.ERROR_FETCHING_RELEASES = "রিলিজগুলি আনতে ত্রুটি: {0}" self.CONFIRM_DELETION_TITLE = "মুছে ফেলা নিশ্চিত করুন" self.LOG_FOR = "{0} এর জন্য লগ" self.ALL_FILES = "সমস্ত ফাইল (*)" self.GGUF_FILES = "GGUF ফাইল (*.gguf)" self.DAT_FILES = "DAT ফাইল (*.dat)" self.JSON_FILES = "JSON ফাইল (*.json)" self.FAILED_LOAD_PRESET = "প্রিসেট লোড করতে ব্যর্থ: {0}" self.INITIALIZING_AUTOGGUF = "AutoGGUF অ্যাপ্লিকেশন শুরু হচ্ছে" self.AUTOGGUF_INITIALIZATION_COMPLETE = "AutoGGUF ইনিশিয়ালাইজেশন সম্পন্ন" self.REFRESHING_BACKENDS = "ব্যাকএন্ডগুলি রিফ্রেশ করা হচ্ছে" self.NO_BACKENDS_AVAILABLE = "কোন ব্যাকএন্ড উপলব্ধ নেই" self.FOUND_VALID_BACKENDS = "{0} টি বৈধ ব্যাকএন্ড পাওয়া গেছে" self.SAVING_PRESET = "প্রিসেট সংরক্ষণ করা হচ্ছে" self.PRESET_SAVED_TO = "{0} এ প্রিসেট সংরক্ষিত" self.LOADING_PRESET = "প্রিসেট লোড করা হচ্ছে" self.PRESET_LOADED_FROM = "{0} থেকে প্রিসেট লোড করা হয়েছে" self.ADDING_KV_OVERRIDE = "KV ওভাররাইড যুক্ত করা হচ্ছে: {0}" self.SAVING_TASK_PRESET = "{0} এর জন্য টাস্ক প্রিসেট সংরক্ষণ করা হচ্ছে" self.TASK_PRESET_SAVED = "টাস্ক প্রিসেট সংরক্ষিত" self.TASK_PRESET_SAVED_TO = "{0} এ টাস্ক প্রিসেট সংরক্ষিত" self.RESTARTING_TASK = "টাস্ক পুনরায় শুরু করা হচ্ছে: {0}" self.IN_PROGRESS = "চলছে" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "ডাউনলোড সম্পন্ন। বের করা হয়েছে: {0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "llama.cpp বাইনারি ফাইল ডাউনলোড এবং {0} এ বের করা হয়েছে\nCUDA ফাইলগুলি {1} এ বের করা হয়েছে" self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "এক্সট্র্যাকশনের জন্য কোন উপযুক্ত CUDA ব্যাকএন্ড পাওয়া যায়নি" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "llama.cpp বাইনারি ফাইল ডাউনলোড এবং {0} এ বের করা হয়েছে" ) self.REFRESHING_LLAMACPP_RELEASES = "llama.cpp রিলিজগুলি রিফ্রেশ করা হচ্ছে" self.UPDATING_ASSET_LIST = "অ্যাসেট তালিকা আপডেট করা হচ্ছে" self.UPDATING_CUDA_OPTIONS = "CUDA অপশনগুলি আপডেট করা হচ্ছে" self.STARTING_LLAMACPP_DOWNLOAD = "llama.cpp ডাউনলোড শুরু করা হচ্ছে" self.UPDATING_CUDA_BACKENDS = "CUDA ব্যাকএন্ডগুলি আপডেট করা হচ্ছে" self.NO_CUDA_BACKEND_SELECTED = ( "এক্সট্র্যাকশনের জন্য কোন CUDA ব্যাকএন্ড নির্বাচন করা হয়নি" ) self.EXTRACTING_CUDA_FILES = "{0} থেকে {1} এ CUDA ফাইলগুলি বের করা হচ্ছে" self.DOWNLOAD_ERROR = "ডাউনলোড ত্রুটি: {0}" self.SHOWING_TASK_CONTEXT_MENU = "টাস্ক কনটেক্সট মেনু দেখানো হচ্ছে" self.SHOWING_PROPERTIES_FOR_TASK = "টাস্কের জন্য বৈশিষ্ট্য দেখানো হচ্ছে: {0}" self.CANCELLING_TASK = "টাস্ক বাতিল করা হচ্ছে: {0}" self.CANCELED = "বাতিল করা হয়েছে" self.DELETING_TASK = "টাস্ক মুছে ফেলা হচ্ছে: {0}" self.LOADING_MODELS = "মডেলগুলি লোড করা হচ্ছে" self.LOADED_MODELS = "{0} টি মডেল লোড করা হয়েছে" self.BROWSING_FOR_MODELS_DIRECTORY = "মডেল ডিরেক্টরি ব্রাউজ করা হচ্ছে" self.SELECT_MODELS_DIRECTORY = "মডেল ডিরেক্টরি নির্বাচন করুন" self.BROWSING_FOR_OUTPUT_DIRECTORY = "আউটপুট ডিরেক্টরি ব্রাউজ করা হচ্ছে" self.SELECT_OUTPUT_DIRECTORY = "আউটপুট ডিরেক্টরি নির্বাচন করুন" self.BROWSING_FOR_LOGS_DIRECTORY = "লগ ডিরেক্টরি ব্রাউজ করা হচ্ছে" self.SELECT_LOGS_DIRECTORY = "লগ ডিরেক্টরি নির্বাচন করুন" self.BROWSING_FOR_IMATRIX_FILE = "IMatrix ফাইল ব্রাউজ করা হচ্ছে" self.SELECT_IMATRIX_FILE = "IMatrix ফাইল নির্বাচন করুন" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "CPU ব্যবহার: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "কোয়ান্টাইজেশন ইনপুট যাচাই করা হচ্ছে" self.MODELS_PATH_REQUIRED = "মডেল পাথ প্রয়োজন" self.OUTPUT_PATH_REQUIRED = "আউটপুট পাথ প্রয়োজন" self.LOGS_PATH_REQUIRED = "লগ পাথ প্রয়োজন" self.STARTING_MODEL_QUANTIZATION = "মডেল কোয়ান্টাইজেশন শুরু হচ্ছে" self.INPUT_FILE_NOT_EXIST = "ইনপুট ফাইল '{0}' বিদ্যমান নেই।" self.QUANTIZING_MODEL_TO = "{0} কে {1} এ কোয়ান্টাইজ করা হচ্ছে" self.QUANTIZATION_TASK_STARTED = "{0} এর জন্য কোয়ান্টাইজেশন টাস্ক শুরু হয়েছে" self.ERROR_STARTING_QUANTIZATION = "কোয়ান্টাইজেশন শুরু করতে ত্রুটি: {0}" self.UPDATING_MODEL_INFO = "মডেল তথ্য আপডেট করা হচ্ছে: {0}" self.TASK_FINISHED = "টাস্ক সম্পন্ন: {0}" self.SHOWING_TASK_DETAILS_FOR = "এর জন্য টাস্কের বিবরণ দেখানো হচ্ছে: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "IMatrix ডেটা ফাইল ব্রাউজ করা হচ্ছে" self.SELECT_DATA_FILE = "ডেটা ফাইল নির্বাচন করুন" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "IMatrix মডেল ফাইল ব্রাউজ করা হচ্ছে" self.SELECT_MODEL_FILE = "মডেল ফাইল নির্বাচন করুন" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "IMatrix আউটপুট ফাইল ব্রাউজ করা হচ্ছে" self.SELECT_OUTPUT_FILE = "আউটপুট ফাইল নির্বাচন করুন" self.STARTING_IMATRIX_GENERATION = "IMatrix জেনারেশন শুরু হচ্ছে" self.BACKEND_PATH_NOT_EXIST = "ব্যাকএন্ড পাথ বিদ্যমান নেই: {0}" self.GENERATING_IMATRIX = "IMatrix তৈরি করা হচ্ছে" self.ERROR_STARTING_IMATRIX_GENERATION = "IMatrix জেনারেশন শুরু করতে ত্রুটি: {0}" self.IMATRIX_GENERATION_TASK_STARTED = "IMatrix জেনারেশন টাস্ক শুরু হয়েছে" self.ERROR_MESSAGE = "ত্রুটি: {0}" self.TASK_ERROR = "টাস্ক ত্রুটি: {0}" self.APPLICATION_CLOSING = "অ্যাপ্লিকেশন বন্ধ করা হচ্ছে" self.APPLICATION_CLOSED = "অ্যাপ্লিকেশন বন্ধ" self.SELECT_QUANTIZATION_TYPE = "কোয়ান্টাইজেশন ধরণ নির্বাচন করুন" self.ALLOWS_REQUANTIZING = "যে টেন্সরগুলি ইতিমধ্যে কোয়ান্টাইজ করা হয়েছে তাদের পুনরায় কোয়ান্টাইজ করার অনুমতি দেয়" self.LEAVE_OUTPUT_WEIGHT = "output.weight কে (পুনরায়) কোয়ান্টাইজ না করে রেখে দেবে" self.DISABLE_K_QUANT_MIXTURES = ( "k-কোয়ান্ট মিশ্রণগুলি অক্ষম করুন এবং সমস্ত টেন্সরকে একই ধরণের কোয়ান্টাইজ করুন" ) self.USE_DATA_AS_IMPORTANCE_MATRIX = ( "কোয়ান্ট অপ্টিমাইজেশনের জন্য ফাইলের ডেটা গুরুত্বপূর্ণ ম্যাট্রিক্স হিসাবে ব্যবহার করুন" ) self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "এই টেন্সরগুলির জন্য গুরুত্বপূর্ণ ম্যাট্রিক্স ব্যবহার করুন" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "এই টেন্সরগুলির জন্য গুরুত্বপূর্ণ ম্যাট্রিক্স ব্যবহার করবেন না" ) self.OUTPUT_TENSOR_TYPE = "আউটপুট টেন্সর ধরণ:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "output.weight টেন্সরের জন্য এই ধরণটি ব্যবহার করুন" ) self.TOKEN_EMBEDDING_TYPE = "টোকেন এম্বেডিং ধরণ:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "টোকেন এম্বেডিং টেন্সরের জন্য এই ধরণটি ব্যবহার করুন" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "ইনপুটের মতো একই শার্ডে কোয়ান্টাইজ করা মডেল তৈরি করবে" ) self.OVERRIDE_MODEL_METADATA = "মডেল মেটাডেটা ওভাররাইড করুন" self.INPUT_DATA_FILE_FOR_IMATRIX = "IMatrix জেনারেশনের জন্য ইনপুট ডেটা ফাইল" self.MODEL_TO_BE_QUANTIZED = "কোয়ান্টাইজ করার জন্য মডেল" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = "তৈরি করা IMatrix এর জন্য আউটপুট পাথ" self.HOW_OFTEN_TO_SAVE_IMATRIX = "IMatrix কতবার সংরক্ষণ করবেন" self.SET_GPU_OFFLOAD_VALUE = "GPU অফলোড মান সেট করুন (-ngl)" self.COMPLETED = "সম্পন্ন" self.REFRESH_MODELS = "মডেল রিফ্রেশ করুন" class _Polish(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (Automatyczny kwantyzator modeli GGUF)" self.RAM_USAGE = "Użycie pamięci RAM:" self.CPU_USAGE = "Użycie procesora:" self.BACKEND = "Backend Llama.cpp:" self.REFRESH_BACKENDS = "Odśwież backendy" self.MODELS_PATH = "Ścieżka modeli:" self.OUTPUT_PATH = "Ścieżka wyjściowa:" self.LOGS_PATH = "Ścieżka logów:" self.BROWSE = "Przeglądaj" self.AVAILABLE_MODELS = "Dostępne modele:" self.QUANTIZATION_TYPE = "Typ kwantyzacji:" self.ALLOW_REQUANTIZE = "Zezwól na ponowną kwantyzację" self.LEAVE_OUTPUT_TENSOR = "Pozostaw tensor wyjściowy" self.PURE = "Czysty" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "Uwzględnij wagi:" self.EXCLUDE_WEIGHTS = "Wyklucz wagi:" self.USE_OUTPUT_TENSOR_TYPE = "Użyj typu tensora wyjściowego" self.USE_TOKEN_EMBEDDING_TYPE = "Użyj typu osadzania tokenów" self.KEEP_SPLIT = "Zachowaj podział" self.KV_OVERRIDES = "Nadpisania KV:" self.ADD_NEW_OVERRIDE = "Dodaj nowe nadpisanie" self.QUANTIZE_MODEL = "Kwantyzuj model" self.SAVE_PRESET = "Zapisz ustawienia predefiniowane" self.LOAD_PRESET = "Wczytaj ustawienia predefiniowane" self.TASKS = "Zadania:" self.DOWNLOAD_LLAMACPP = "Pobierz llama.cpp" self.SELECT_RELEASE = "Wybierz wersję:" self.SELECT_ASSET = "Wybierz zasób:" self.EXTRACT_CUDA_FILES = "Wyodrębnij pliki CUDA" self.SELECT_CUDA_BACKEND = "Wybierz backend CUDA:" self.DOWNLOAD = "Pobierz" self.IMATRIX_GENERATION = "Generowanie IMatrix" self.DATA_FILE = "Plik danych:" self.MODEL = "Model:" self.OUTPUT = "Wyjście:" self.OUTPUT_FREQUENCY = "Częstotliwość wyjścia:" self.GPU_OFFLOAD = "Odciążenie GPU:" self.AUTO = "Automatyczny" self.GENERATE_IMATRIX = "Generuj IMatrix" self.ERROR = "Błąd" self.WARNING = "Ostrzeżenie" self.PROPERTIES = "Właściwości" self.CANCEL = "Anuluj" self.RESTART = "Uruchom ponownie" self.DELETE = "Usuń" self.CONFIRM_DELETION = "Czy na pewno chcesz usunąć to zadanie?" self.TASK_RUNNING_WARNING = ( "Niektóre zadania są nadal uruchomione. Czy na pewno chcesz wyjść?" ) self.YES = "Tak" self.NO = "Nie" self.DOWNLOAD_COMPLETE = "Pobieranie zakończone" self.CUDA_EXTRACTION_FAILED = "Wyodrębnianie CUDA nie powiodło się" self.PRESET_SAVED = "Ustawienia predefiniowane zapisane" self.PRESET_LOADED = "Ustawienia predefiniowane wczytane" self.NO_ASSET_SELECTED = "Nie wybrano zasobu" self.DOWNLOAD_FAILED = "Pobieranie nie powiodło się" self.NO_BACKEND_SELECTED = "Nie wybrano backendu" self.NO_MODEL_SELECTED = "Nie wybrano modelu" self.REFRESH_RELEASES = "Odśwież wersje" self.NO_SUITABLE_CUDA_BACKENDS = "Nie znaleziono odpowiednich backendów CUDA" self.LLAMACPP_DOWNLOADED_EXTRACTED = "Plik binarny llama.cpp został pobrany i wyodrębniony do {0}\nPliki CUDA wyodrębnione do {1}" self.CUDA_FILES_EXTRACTED = "Pliki CUDA wyodrębnione do" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "Nie znaleziono odpowiedniego backendu CUDA do wyodrębnienia" ) self.ERROR_FETCHING_RELEASES = "Błąd podczas pobierania wersji: {0}" self.CONFIRM_DELETION_TITLE = "Potwierdź usunięcie" self.LOG_FOR = "Dziennik dla {0}" self.ALL_FILES = "Wszystkie pliki (*)" self.GGUF_FILES = "Pliki GGUF (*.gguf)" self.DAT_FILES = "Pliki DAT (*.dat)" self.JSON_FILES = "Pliki JSON (*.json)" self.FAILED_LOAD_PRESET = "Nie udało się wczytać ustawień predefiniowanych: {0}" self.INITIALIZING_AUTOGGUF = "Inicjalizacja aplikacji AutoGGUF" self.AUTOGGUF_INITIALIZATION_COMPLETE = "Inicjalizacja AutoGGUF zakończona" self.REFRESHING_BACKENDS = "Odświeżanie backendów" self.NO_BACKENDS_AVAILABLE = "Brak dostępnych backendów" self.FOUND_VALID_BACKENDS = "Znaleziono {0} prawidłowych backendów" self.SAVING_PRESET = "Zapisywanie ustawień predefiniowanych" self.PRESET_SAVED_TO = "Ustawienia predefiniowane zapisane do {0}" self.LOADING_PRESET = "Wczytywanie ustawień predefiniowanych" self.PRESET_LOADED_FROM = "Ustawienia predefiniowane wczytane z {0}" self.ADDING_KV_OVERRIDE = "Dodawanie nadpisania KV: {0}" self.SAVING_TASK_PRESET = ( "Zapisywanie ustawień predefiniowanych zadania dla {0}" ) self.TASK_PRESET_SAVED = "Ustawienia predefiniowane zadania zapisane" self.TASK_PRESET_SAVED_TO = "Ustawienia predefiniowane zadania zapisane do {0}" self.RESTARTING_TASK = "Ponowne uruchamianie zadania: {0}" self.IN_PROGRESS = "W trakcie" self.DOWNLOAD_FINISHED_EXTRACTED_TO = ( "Pobieranie zakończone. Wyodrębniono do: {0}" ) self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "Plik binarny llama.cpp został pobrany i wyodrębniony do {0}\nPliki CUDA wyodrębnione do {1}" self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "Nie znaleziono odpowiedniego backendu CUDA do wyodrębnienia" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "Plik binarny llama.cpp został pobrany i wyodrębniony do {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "Odświeżanie wersji llama.cpp" self.UPDATING_ASSET_LIST = "Aktualizacja listy zasobów" self.UPDATING_CUDA_OPTIONS = "Aktualizacja opcji CUDA" self.STARTING_LLAMACPP_DOWNLOAD = "Rozpoczynanie pobierania llama.cpp" self.UPDATING_CUDA_BACKENDS = "Aktualizacja backendów CUDA" self.NO_CUDA_BACKEND_SELECTED = "Nie wybrano backendu CUDA do wyodrębnienia" self.EXTRACTING_CUDA_FILES = "Wyodrębnianie plików CUDA z {0} do {1}" self.DOWNLOAD_ERROR = "Błąd pobierania: {0}" self.SHOWING_TASK_CONTEXT_MENU = "Wyświetlanie menu kontekstowego zadania" self.SHOWING_PROPERTIES_FOR_TASK = "Wyświetlanie właściwości zadania: {0}" self.CANCELLING_TASK = "Anulowanie zadania: {0}" self.CANCELED = "Anulowano" self.DELETING_TASK = "Usuwanie zadania: {0}" self.LOADING_MODELS = "Ładowanie modeli" self.LOADED_MODELS = "Załadowano {0} modeli" self.BROWSING_FOR_MODELS_DIRECTORY = "Przeglądanie katalogu modeli" self.SELECT_MODELS_DIRECTORY = "Wybierz katalog modeli" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Przeglądanie katalogu wyjściowego" self.SELECT_OUTPUT_DIRECTORY = "Wybierz katalog wyjściowy" self.BROWSING_FOR_LOGS_DIRECTORY = "Przeglądanie katalogu logów" self.SELECT_LOGS_DIRECTORY = "Wybierz katalog logów" self.BROWSING_FOR_IMATRIX_FILE = "Przeglądanie pliku IMatrix" self.SELECT_IMATRIX_FILE = "Wybierz plik IMatrix" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "Użycie procesora: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "Walidacja danych wejściowych kwantyzacji" self.MODELS_PATH_REQUIRED = "Ścieżka modeli jest wymagana" self.OUTPUT_PATH_REQUIRED = "Ścieżka wyjściowa jest wymagana" self.LOGS_PATH_REQUIRED = "Ścieżka logów jest wymagana" self.STARTING_MODEL_QUANTIZATION = "Rozpoczynanie kwantyzacji modelu" self.INPUT_FILE_NOT_EXIST = "Plik wejściowy '{0}' nie istnieje." self.QUANTIZING_MODEL_TO = "Kwantyzacja {0} do {1}" self.QUANTIZATION_TASK_STARTED = "Zadanie kwantyzacji uruchomione dla {0}" self.ERROR_STARTING_QUANTIZATION = "Błąd podczas uruchamiania kwantyzacji: {0}" self.UPDATING_MODEL_INFO = "Aktualizacja informacji o modelu: {0}" self.TASK_FINISHED = "Zadanie zakończone: {0}" self.SHOWING_TASK_DETAILS_FOR = "Wyświetlanie szczegółów zadania dla: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "Przeglądanie pliku danych IMatrix" self.SELECT_DATA_FILE = "Wybierz plik danych" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "Przeglądanie pliku modelu IMatrix" self.SELECT_MODEL_FILE = "Wybierz plik modelu" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "Przeglądanie pliku wyjściowego IMatrix" self.SELECT_OUTPUT_FILE = "Wybierz plik wyjściowy" self.STARTING_IMATRIX_GENERATION = "Rozpoczynanie generowania IMatrix" self.BACKEND_PATH_NOT_EXIST = "Ścieżka backendu nie istnieje: {0}" self.GENERATING_IMATRIX = "Generowanie IMatrix" self.ERROR_STARTING_IMATRIX_GENERATION = ( "Błąd podczas uruchamiania generowania IMatrix: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "Zadanie generowania IMatrix uruchomione" self.ERROR_MESSAGE = "Błąd: {0}" self.TASK_ERROR = "Błąd zadania: {0}" self.APPLICATION_CLOSING = "Zamykanie aplikacji" self.APPLICATION_CLOSED = "Aplikacja zamknięta" self.SELECT_QUANTIZATION_TYPE = "Wybierz typ kwantyzacji" self.ALLOWS_REQUANTIZING = ( "Pozwala na ponowną kwantyzację tensorów, które zostały już skwantyzowane" ) self.LEAVE_OUTPUT_WEIGHT = ( "Pozostawi output.weight nieskwantyzowany (lub nieskwantyzowany ponownie)" ) self.DISABLE_K_QUANT_MIXTURES = ( "Wyłącz mieszanki k-kwant i kwantyzuj wszystkie tensory do tego samego typu" ) self.USE_DATA_AS_IMPORTANCE_MATRIX = ( "Użyj danych w pliku jako macierzy ważności dla optymalizacji kwantyzacji" ) self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Użyj macierzy ważności dla tych tensorów" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Nie używaj macierzy ważności dla tych tensorów" ) self.OUTPUT_TENSOR_TYPE = "Typ tensora wyjściowego:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Użyj tego typu dla tensora output.weight" ) self.TOKEN_EMBEDDING_TYPE = "Typ osadzania tokenów:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Użyj tego typu dla tensora osadzania tokenów" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "Wygeneruje skwantyzowany model w tych samych fragmentach co dane wejściowe" ) self.OVERRIDE_MODEL_METADATA = "Zastąp metadane modelu" self.INPUT_DATA_FILE_FOR_IMATRIX = ( "Plik danych wejściowych do generowania IMatrix" ) self.MODEL_TO_BE_QUANTIZED = "Model do kwantyzacji" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = ( "Ścieżka wyjściowa dla wygenerowanego IMatrix" ) self.HOW_OFTEN_TO_SAVE_IMATRIX = "Jak często zapisywać IMatrix" self.SET_GPU_OFFLOAD_VALUE = "Ustaw wartość odciążenia GPU (-ngl)" self.COMPLETED = "Ukończono" self.REFRESH_MODELS = "Obnovit modely" class _Romanian(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (Cuantizator automat de modele GGUF)" self.RAM_USAGE = "Utilizare RAM:" self.CPU_USAGE = "Utilizare CPU:" self.BACKEND = "Backend Llama.cpp:" self.REFRESH_BACKENDS = "Reîmprospătați backends" self.MODELS_PATH = "Cale modele:" self.OUTPUT_PATH = "Cale ieșire:" self.LOGS_PATH = "Cale jurnale:" self.BROWSE = "Răsfoiți" self.AVAILABLE_MODELS = "Modele disponibile:" self.QUANTIZATION_TYPE = "Tipul de cuantizare:" self.ALLOW_REQUANTIZE = "Permiteți recuantizarea" self.LEAVE_OUTPUT_TENSOR = "Lăsați tensorul de ieșire" self.PURE = "Pur" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "Includeți ponderile:" self.EXCLUDE_WEIGHTS = "Excludeți ponderile:" self.USE_OUTPUT_TENSOR_TYPE = "Utilizați tipul tensorului de ieșire" self.USE_TOKEN_EMBEDDING_TYPE = "Utilizați tipul de încorporare a tokenului" self.KEEP_SPLIT = "Păstrați divizarea" self.KV_OVERRIDES = "Suprascrieri KV:" self.ADD_NEW_OVERRIDE = "Adăugați o nouă suprascriere" self.QUANTIZE_MODEL = "Cuantizați modelul" self.SAVE_PRESET = "Salvați presetarea" self.LOAD_PRESET = "Încărcați presetarea" self.TASKS = "Sarcini:" self.DOWNLOAD_LLAMACPP = "Descărcați llama.cpp" self.SELECT_RELEASE = "Selectați versiunea:" self.SELECT_ASSET = "Selectați activul:" self.EXTRACT_CUDA_FILES = "Extrageți fișierele CUDA" self.SELECT_CUDA_BACKEND = "Selectați backend CUDA:" self.DOWNLOAD = "Descărcați" self.IMATRIX_GENERATION = "Generare IMatrix" self.DATA_FILE = "Fișier de date:" self.MODEL = "Model:" self.OUTPUT = "Ieșire:" self.OUTPUT_FREQUENCY = "Frecvența ieșirii:" self.GPU_OFFLOAD = "Descărcare GPU:" self.AUTO = "Automat" self.GENERATE_IMATRIX = "Generați IMatrix" self.ERROR = "Eroare" self.WARNING = "Avertisment" self.PROPERTIES = "Proprietăți" self.CANCEL = "Anulați" self.RESTART = "Reporniți" self.DELETE = "Ștergeți" self.CONFIRM_DELETION = "Sunteți sigur că doriți să ștergeți această sarcină?" self.TASK_RUNNING_WARNING = "Unele sarcini sunt încă în curs de execuție. Sunteți sigur că doriți să ieșiți?" self.YES = "Da" self.NO = "Nu" self.DOWNLOAD_COMPLETE = "Descărcare finalizată" self.CUDA_EXTRACTION_FAILED = "Extragerea CUDA a eșuat" self.PRESET_SAVED = "Presetare salvată" self.PRESET_LOADED = "Presetare încărcată" self.NO_ASSET_SELECTED = "Niciun activ selectat" self.DOWNLOAD_FAILED = "Descărcarea a eșuat" self.NO_BACKEND_SELECTED = "Niciun backend selectat" self.NO_MODEL_SELECTED = "Niciun model selectat" self.REFRESH_RELEASES = "Reîmprospătați versiunile" self.NO_SUITABLE_CUDA_BACKENDS = "Nu s-au găsit backends CUDA potrivite" self.LLAMACPP_DOWNLOADED_EXTRACTED = "Fișierul binar llama.cpp a fost descărcat și extras în {0}\nFișierele CUDA au fost extrase în {1}" self.CUDA_FILES_EXTRACTED = "Fișierele CUDA au fost extrase în" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "Nu s-a găsit un backend CUDA potrivit pentru extragere" ) self.ERROR_FETCHING_RELEASES = "Eroare la preluarea versiunilor: {0}" self.CONFIRM_DELETION_TITLE = "Confirmați ștergerea" self.LOG_FOR = "Jurnal pentru {0}" self.ALL_FILES = "Toate fișierele (*)" self.GGUF_FILES = "Fișiere GGUF (*.gguf)" self.DAT_FILES = "Fișiere DAT (*.dat)" self.JSON_FILES = "Fișiere JSON (*.json)" self.FAILED_LOAD_PRESET = "Nu s-a putut încărca presetarea: {0}" self.INITIALIZING_AUTOGGUF = "Inițializarea aplicației AutoGGUF" self.AUTOGGUF_INITIALIZATION_COMPLETE = "Inițializarea AutoGGUF finalizată" self.REFRESHING_BACKENDS = "Reîmprospătarea backends" self.NO_BACKENDS_AVAILABLE = "Nu există backends disponibile" self.FOUND_VALID_BACKENDS = "S-au găsit {0} backends valide" self.SAVING_PRESET = "Salvarea presetării" self.PRESET_SAVED_TO = "Presetare salvată în {0}" self.LOADING_PRESET = "Încărcarea presetării" self.PRESET_LOADED_FROM = "Presetare încărcată din {0}" self.ADDING_KV_OVERRIDE = "Adăugarea suprascrierii KV: {0}" self.SAVING_TASK_PRESET = "Salvarea presetării sarcinii pentru {0}" self.TASK_PRESET_SAVED = "Presetare sarcină salvată" self.TASK_PRESET_SAVED_TO = "Presetare sarcină salvată în {0}" self.RESTARTING_TASK = "Repornirea sarcinii: {0}" self.IN_PROGRESS = "În curs" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "Descărcare finalizată. Extras în: {0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "Fișierul binar llama.cpp a fost descărcat și extras în {0}\nFișierele CUDA au fost extrase în {1}" self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "Nu s-a găsit un backend CUDA potrivit pentru extragere" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "Fișierul binar llama.cpp a fost descărcat și extras în {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "Reîmprospătarea versiunilor llama.cpp" self.UPDATING_ASSET_LIST = "Actualizarea listei de active" self.UPDATING_CUDA_OPTIONS = "Actualizarea opțiunilor CUDA" self.STARTING_LLAMACPP_DOWNLOAD = "Începerea descărcării llama.cpp" self.UPDATING_CUDA_BACKENDS = "Actualizarea backends CUDA" self.NO_CUDA_BACKEND_SELECTED = "Niciun backend CUDA selectat pentru extragere" self.EXTRACTING_CUDA_FILES = "Extragerea fișierelor CUDA din {0} în {1}" self.DOWNLOAD_ERROR = "Eroare de descărcare: {0}" self.SHOWING_TASK_CONTEXT_MENU = "Afișarea meniului contextual al sarcinii" self.SHOWING_PROPERTIES_FOR_TASK = "Afișarea proprietăților pentru sarcina: {0}" self.CANCELLING_TASK = "Anularea sarcinii: {0}" self.CANCELED = "Anulat" self.DELETING_TASK = "Ștergerea sarcinii: {0}" self.LOADING_MODELS = "Încărcarea modelelor" self.LOADED_MODELS = "{0} modele încărcate" self.BROWSING_FOR_MODELS_DIRECTORY = "Răsfoirea directorului de modele" self.SELECT_MODELS_DIRECTORY = "Selectați directorul de modele" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Răsfoirea directorului de ieșire" self.SELECT_OUTPUT_DIRECTORY = "Selectați directorul de ieșire" self.BROWSING_FOR_LOGS_DIRECTORY = "Răsfoirea directorului de jurnale" self.SELECT_LOGS_DIRECTORY = "Selectați directorul de jurnale" self.BROWSING_FOR_IMATRIX_FILE = "Răsfoirea fișierului IMatrix" self.SELECT_IMATRIX_FILE = "Selectați fișierul IMatrix" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "Utilizare CPU: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "Validarea intrărilor de cuantizare" self.MODELS_PATH_REQUIRED = "Calea modelelor este obligatorie" self.OUTPUT_PATH_REQUIRED = "Calea ieșirii este obligatorie" self.LOGS_PATH_REQUIRED = "Calea jurnalelor este obligatorie" self.STARTING_MODEL_QUANTIZATION = "Pornirea cuantizării modelului" self.INPUT_FILE_NOT_EXIST = "Fișierul de intrare '{0}' nu există." self.QUANTIZING_MODEL_TO = "Cuantizarea {0} la {1}" self.QUANTIZATION_TASK_STARTED = ( "Sarcina de cuantizare a fost pornită pentru {0}" ) self.ERROR_STARTING_QUANTIZATION = "Eroare la pornirea cuantizării: {0}" self.UPDATING_MODEL_INFO = "Actualizarea informațiilor despre model: {0}" self.TASK_FINISHED = "Sarcină finalizată: {0}" self.SHOWING_TASK_DETAILS_FOR = "Afișarea detaliilor sarcinii pentru: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "Răsfoirea fișierului de date IMatrix" self.SELECT_DATA_FILE = "Selectați fișierul de date" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "Răsfoirea fișierului de model IMatrix" self.SELECT_MODEL_FILE = "Selectați fișierul model" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "Răsfoirea fișierului de ieșire IMatrix" self.SELECT_OUTPUT_FILE = "Selectați fișierul de ieșire" self.STARTING_IMATRIX_GENERATION = "Pornirea generării IMatrix" self.BACKEND_PATH_NOT_EXIST = "Calea backendului nu există: {0}" self.GENERATING_IMATRIX = "Generarea IMatrix" self.ERROR_STARTING_IMATRIX_GENERATION = ( "Eroare la pornirea generării IMatrix: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = ( "Sarcina de generare IMatrix a fost pornită" ) self.ERROR_MESSAGE = "Eroare: {0}" self.TASK_ERROR = "Eroare de sarcină: {0}" self.APPLICATION_CLOSING = "Închiderea aplicației" self.APPLICATION_CLOSED = "Aplicație închisă" self.SELECT_QUANTIZATION_TYPE = "Selectați tipul de cuantizare" self.ALLOWS_REQUANTIZING = ( "Permite recuantizarea tensorilor care au fost deja cuantizați" ) self.LEAVE_OUTPUT_WEIGHT = "Va lăsa output.weight necuantizat (sau recuantizat)" self.DISABLE_K_QUANT_MIXTURES = ( "Dezactivați mixurile k-quant și cuantizați toți tensorii la același tip" ) self.USE_DATA_AS_IMPORTANCE_MATRIX = "Utilizați datele din fișier ca matrice de importanță pentru optimizările de cuantizare" self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Utilizați matricea de importanță pentru acești tensori" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Nu utilizați matricea de importanță pentru acești tensori" ) self.OUTPUT_TENSOR_TYPE = "Tipul tensorului de ieșire:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Utilizați acest tip pentru tensorul output.weight" ) self.TOKEN_EMBEDDING_TYPE = "Tipul de încorporare a tokenului:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Utilizați acest tip pentru tensorul de încorporări ale tokenului" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "Va genera modelul cuantizat în aceleași fragmente ca și intrarea" ) self.OVERRIDE_MODEL_METADATA = "Suprascrieți metadatele modelului" self.INPUT_DATA_FILE_FOR_IMATRIX = ( "Fișier de date de intrare pentru generarea IMatrix" ) self.MODEL_TO_BE_QUANTIZED = "Modelul de cuantizat" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = ( "Calea de ieșire pentru IMatrix generat" ) self.HOW_OFTEN_TO_SAVE_IMATRIX = "Cât de des să salvați IMatrix" self.SET_GPU_OFFLOAD_VALUE = "Setați valoarea de descărcare GPU (-ngl)" self.COMPLETED = "Finalizat" self.REFRESH_MODELS = "Odśwież modele" class _Czech(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (Automatický kvantizátor modelů GGUF)" self.RAM_USAGE = "Využití RAM:" self.CPU_USAGE = "Využití CPU:" self.BACKEND = "Backend Llama.cpp:" self.REFRESH_BACKENDS = "Obnovit backendy" self.MODELS_PATH = "Cesta k modelům:" self.OUTPUT_PATH = "Výstupní cesta:" self.LOGS_PATH = "Cesta k logům:" self.BROWSE = "Procházet" self.AVAILABLE_MODELS = "Dostupné modely:" self.QUANTIZATION_TYPE = "Typ kvantizace:" self.ALLOW_REQUANTIZE = "Povolit rekvantizaci" self.LEAVE_OUTPUT_TENSOR = "Ponechat výstupní tenzor" self.PURE = "Čistý" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "Zahrnout váhy:" self.EXCLUDE_WEIGHTS = "Vyloučit váhy:" self.USE_OUTPUT_TENSOR_TYPE = "Použít typ výstupního tenzoru" self.USE_TOKEN_EMBEDDING_TYPE = "Použít typ vkládání tokenů" self.KEEP_SPLIT = "Zachovat rozdělení" self.KV_OVERRIDES = "Přepsání KV:" self.ADD_NEW_OVERRIDE = "Přidat nové přepsání" self.QUANTIZE_MODEL = "Kvantizovat model" self.SAVE_PRESET = "Uložit předvolbu" self.LOAD_PRESET = "Načíst předvolbu" self.TASKS = "Úkoly:" self.DOWNLOAD_LLAMACPP = "Stáhnout llama.cpp" self.SELECT_RELEASE = "Vybrat verzi:" self.SELECT_ASSET = "Vybrat aktivum:" self.EXTRACT_CUDA_FILES = "Extrahovat soubory CUDA" self.SELECT_CUDA_BACKEND = "Vybrat backend CUDA:" self.DOWNLOAD = "Stáhnout" self.IMATRIX_GENERATION = "Generování IMatrix" self.DATA_FILE = "Datový soubor:" self.MODEL = "Model:" self.OUTPUT = "Výstup:" self.OUTPUT_FREQUENCY = "Frekvence výstupu:" self.GPU_OFFLOAD = "Odlehčení GPU:" self.AUTO = "Automaticky" self.GENERATE_IMATRIX = "Generovat IMatrix" self.ERROR = "Chyba" self.WARNING = "Varování" self.PROPERTIES = "Vlastnosti" self.CANCEL = "Zrušit" self.RESTART = "Restartovat" self.DELETE = "Smazat" self.CONFIRM_DELETION = "Jste si jisti, že chcete smazat tento úkol?" self.TASK_RUNNING_WARNING = ( "Některé úkoly stále běží. Jste si jisti, že chcete ukončit?" ) self.YES = "Ano" self.NO = "Ne" self.DOWNLOAD_COMPLETE = "Stahování dokončeno" self.CUDA_EXTRACTION_FAILED = "Extrahování CUDA se nezdařilo" self.PRESET_SAVED = "Předvolba uložena" self.PRESET_LOADED = "Předvolba načtena" self.NO_ASSET_SELECTED = "Nebylo vybráno žádné aktivum" self.DOWNLOAD_FAILED = "Stahování se nezdařilo" self.NO_BACKEND_SELECTED = "Nebyl vybrán žádný backend" self.NO_MODEL_SELECTED = "Nebyl vybrán žádný model" self.REFRESH_RELEASES = "Obnovit verze" self.NO_SUITABLE_CUDA_BACKENDS = "Nebyly nalezeny žádné vhodné backendy CUDA" self.LLAMACPP_DOWNLOADED_EXTRACTED = "Binární soubor llama.cpp byl stažen a extrahován do {0}\nSoubory CUDA extrahovány do {1}" self.CUDA_FILES_EXTRACTED = "Soubory CUDA extrahovány do" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "Nebyl nalezen žádný vhodný backend CUDA pro extrakci" ) self.ERROR_FETCHING_RELEASES = "Chyba při načítání verzí: {0}" self.CONFIRM_DELETION_TITLE = "Potvrdit smazání" self.LOG_FOR = "Log pro {0}" self.ALL_FILES = "Všechny soubory (*)" self.GGUF_FILES = "Soubory GGUF (*.gguf)" self.DAT_FILES = "Soubory DAT (*.dat)" self.JSON_FILES = "Soubory JSON (*.json)" self.FAILED_LOAD_PRESET = "Nepodařilo se načíst předvolbu: {0}" self.INITIALIZING_AUTOGGUF = "Inicializace aplikace AutoGGUF" self.AUTOGGUF_INITIALIZATION_COMPLETE = "Inicializace AutoGGUF dokončena" self.REFRESHING_BACKENDS = "Obnovování backendů" self.NO_BACKENDS_AVAILABLE = "Žádné dostupné backendy" self.FOUND_VALID_BACKENDS = "Nalezeno {0} platných backendů" self.SAVING_PRESET = "Ukládání předvolby" self.PRESET_SAVED_TO = "Předvolba uložena do {0}" self.LOADING_PRESET = "Načítání předvolby" self.PRESET_LOADED_FROM = "Předvolba načtena z {0}" self.ADDING_KV_OVERRIDE = "Přidávání přepsání KV: {0}" self.SAVING_TASK_PRESET = "Ukládání předvolby úkolu pro {0}" self.TASK_PRESET_SAVED = "Předvolba úkolu uložena" self.TASK_PRESET_SAVED_TO = "Předvolba úkolu uložena do {0}" self.RESTARTING_TASK = "Restartování úkolu: {0}" self.IN_PROGRESS = "Probíhá" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "Stahování dokončeno. Extrahováno do: {0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "Binární soubor llama.cpp byl stažen a extrahován do {0}\nSoubory CUDA extrahovány do {1}" self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "Nebyl nalezen žádný vhodný backend CUDA pro extrakci" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "Binární soubor llama.cpp byl stažen a extrahován do {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "Obnovování verzí llama.cpp" self.UPDATING_ASSET_LIST = "Aktualizace seznamu aktiv" self.UPDATING_CUDA_OPTIONS = "Aktualizace možností CUDA" self.STARTING_LLAMACPP_DOWNLOAD = "Zahájení stahování llama.cpp" self.UPDATING_CUDA_BACKENDS = "Aktualizace backendů CUDA" self.NO_CUDA_BACKEND_SELECTED = "Nebyl vybrán žádný backend CUDA pro extrakci" self.EXTRACTING_CUDA_FILES = "Extrahování souborů CUDA z {0} do {1}" self.DOWNLOAD_ERROR = "Chyba stahování: {0}" self.SHOWING_TASK_CONTEXT_MENU = "Zobrazení kontextové nabídky úkolu" self.SHOWING_PROPERTIES_FOR_TASK = "Zobrazení vlastností úkolu: {0}" self.CANCELLING_TASK = "Zrušení úkolu: {0}" self.CANCELED = "Zrušeno" self.DELETING_TASK = "Mazání úkolu: {0}" self.LOADING_MODELS = "Načítání modelů" self.LOADED_MODELS = "Načteno {0} modelů" self.BROWSING_FOR_MODELS_DIRECTORY = "Procházení adresáře modelů" self.SELECT_MODELS_DIRECTORY = "Vyberte adresář modelů" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Procházení výstupního adresáře" self.SELECT_OUTPUT_DIRECTORY = "Vyberte výstupní adresář" self.BROWSING_FOR_LOGS_DIRECTORY = "Procházení adresáře logů" self.SELECT_LOGS_DIRECTORY = "Vyberte adresář logů" self.BROWSING_FOR_IMATRIX_FILE = "Procházení souboru IMatrix" self.SELECT_IMATRIX_FILE = "Vyberte soubor IMatrix" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "Využití CPU: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "Ověřování vstupů kvantizace" self.MODELS_PATH_REQUIRED = "Cesta k modelům je vyžadována" self.OUTPUT_PATH_REQUIRED = "Výstupní cesta je vyžadována" self.LOGS_PATH_REQUIRED = "Cesta k logům je vyžadována" self.STARTING_MODEL_QUANTIZATION = "Spuštění kvantizace modelu" self.INPUT_FILE_NOT_EXIST = "Vstupní soubor '{0}' neexistuje." self.QUANTIZING_MODEL_TO = "Kvantizace {0} na {1}" self.QUANTIZATION_TASK_STARTED = "Úkol kvantizace spuštěn pro {0}" self.ERROR_STARTING_QUANTIZATION = "Chyba při spuštění kvantizace: {0}" self.UPDATING_MODEL_INFO = "Aktualizace informací o modelu: {0}" self.TASK_FINISHED = "Úkol dokončen: {0}" self.SHOWING_TASK_DETAILS_FOR = "Zobrazení detailů úkolu pro: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "Procházení datového souboru IMatrix" self.SELECT_DATA_FILE = "Vyberte datový soubor" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "Procházení souboru modelu IMatrix" self.SELECT_MODEL_FILE = "Vyberte soubor modelu" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "Procházení výstupního souboru IMatrix" self.SELECT_OUTPUT_FILE = "Vyberte výstupní soubor" self.STARTING_IMATRIX_GENERATION = "Spuštění generování IMatrix" self.BACKEND_PATH_NOT_EXIST = "Cesta backendu neexistuje: {0}" self.GENERATING_IMATRIX = "Generování IMatrix" self.ERROR_STARTING_IMATRIX_GENERATION = ( "Chyba při spuštění generování IMatrix: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "Úkol generování IMatrix spuštěn" self.ERROR_MESSAGE = "Chyba: {0}" self.TASK_ERROR = "Chyba úkolu: {0}" self.APPLICATION_CLOSING = "Zavírání aplikace" self.APPLICATION_CLOSED = "Aplikace zavřena" self.SELECT_QUANTIZATION_TYPE = "Vyberte typ kvantizace" self.ALLOWS_REQUANTIZING = ( "Umožňuje rekvantizovat tenzory, které již byly kvantizovány" ) self.LEAVE_OUTPUT_WEIGHT = ( "Ponechá output.weight nekvantizovaný (nebo rekvantizovaný)" ) self.DISABLE_K_QUANT_MIXTURES = ( "Zakázat k-kvantové směsi a kvantizovat všechny tenzory na stejný typ" ) self.USE_DATA_AS_IMPORTANCE_MATRIX = ( "Použít data v souboru jako matici důležitosti pro optimalizace kvantizace" ) self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Použít matici důležitosti pro tyto tenzory" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Nepoužívat matici důležitosti pro tyto tenzory" ) self.OUTPUT_TENSOR_TYPE = "Typ výstupního tenzoru:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Použít tento typ pro tenzor output.weight" ) self.TOKEN_EMBEDDING_TYPE = "Typ vkládání tokenů:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Použít tento typ pro tenzor vkládání tokenů" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "Vygeneruje kvantizovaný model ve stejných fragmentech jako vstup" ) self.OVERRIDE_MODEL_METADATA = "Přepsat metadata modelu" self.INPUT_DATA_FILE_FOR_IMATRIX = ( "Vstupní datový soubor pro generování IMatrix" ) self.MODEL_TO_BE_QUANTIZED = "Model, který má být kvantizován" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = "Výstupní cesta pro generovaný IMatrix" self.HOW_OFTEN_TO_SAVE_IMATRIX = "Jak často ukládat IMatrix" self.SET_GPU_OFFLOAD_VALUE = "Nastavit hodnotu odlehčení GPU (-ngl)" self.COMPLETED = "Dokončeno" self.REFRESH_MODELS = "Reîmprospătează modelele" class _CanadianFrench(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (Quantificateur automatique de modèles GGUF)" self.RAM_USAGE = "Utilisation de la RAM :" # Spacing self.CPU_USAGE = "Utilisation du CPU :" # Spacing self.BACKEND = "Moteur d'arrière-plan Llama.cpp :" # Spacing and terminology self.REFRESH_BACKENDS = "Actualiser les moteurs d'arrière-plan" self.MODELS_PATH = "Chemin des modèles :" # Spacing self.OUTPUT_PATH = "Chemin de sortie :" # Spacing self.LOGS_PATH = "Chemin des journaux :" # Spacing self.BROWSE = "Parcourir" self.AVAILABLE_MODELS = "Modèles disponibles :" # Spacing self.QUANTIZATION_TYPE = "Type de quantification :" # Spacing self.ALLOW_REQUANTIZE = "Autoriser la requantification" self.LEAVE_OUTPUT_TENSOR = "Laisser le tenseur de sortie" self.PURE = "Pur" self.IMATRIX = "IMatrix :" # Spacing self.INCLUDE_WEIGHTS = "Inclure les poids :" # Spacing self.EXCLUDE_WEIGHTS = "Exclure les poids :" # Spacing self.USE_OUTPUT_TENSOR_TYPE = "Utiliser le type de tenseur de sortie" self.USE_TOKEN_EMBEDDING_TYPE = "Utiliser le type d'intégration de jeton" self.KEEP_SPLIT = "Conserver la division" self.KV_OVERRIDES = "Remplacements KV :" # Spacing self.ADD_NEW_OVERRIDE = "Ajouter un nouveau remplacement" self.QUANTIZE_MODEL = "Quantifier le modèle" self.SAVE_PRESET = "Enregistrer le préréglage" self.LOAD_PRESET = "Charger le préréglage" self.TASKS = "Tâches :" # Spacing self.DOWNLOAD_LLAMACPP = "Télécharger llama.cpp" self.SELECT_RELEASE = "Sélectionner la version :" # Spacing self.SELECT_ASSET = "Sélectionner l'actif :" # Spacing self.EXTRACT_CUDA_FILES = "Extraire les fichiers CUDA" self.SELECT_CUDA_BACKEND = "Sélectionner le backend CUDA :" # Spacing self.DOWNLOAD = "Télécharger" self.IMATRIX_GENERATION = "Génération d'IMatrix" self.DATA_FILE = "Fichier de données :" # Spacing self.MODEL = "Modèle :" # Spacing self.OUTPUT = "Sortie :" # Spacing self.OUTPUT_FREQUENCY = "Fréquence de sortie :" # Spacing self.GPU_OFFLOAD = "Déchargement GPU :" # Spacing self.AUTO = "Auto" self.GENERATE_IMATRIX = "Générer IMatrix" self.ERROR = "Erreur" self.WARNING = "Avertissement" self.PROPERTIES = "Propriétés" self.CANCEL = "Annuler" self.RESTART = "Redémarrer" self.DELETE = "Supprimer" self.CONFIRM_DELETION = ( "Êtes-vous sûr de vouloir supprimer cette tâche ?" # Spacing ) self.TASK_RUNNING_WARNING = "Certaines tâches sont encore en cours d'exécution. Êtes-vous sûr de vouloir quitter ?" # Spacing self.YES = "Oui" self.NO = "Non" self.DOWNLOAD_COMPLETE = "Téléchargement terminé" self.CUDA_EXTRACTION_FAILED = "Échec de l'extraction CUDA" self.PRESET_SAVED = "Préréglage enregistré" self.PRESET_LOADED = "Préréglage chargé" self.NO_ASSET_SELECTED = "Aucun actif sélectionné" self.DOWNLOAD_FAILED = "Échec du téléchargement" self.NO_BACKEND_SELECTED = "Aucun backend sélectionné" self.NO_MODEL_SELECTED = "Aucun modèle sélectionné" self.REFRESH_RELEASES = "Actualiser les versions" self.NO_SUITABLE_CUDA_BACKENDS = "Aucun backend CUDA approprié trouvé" self.LLAMACPP_DOWNLOADED_EXTRACTED = "Le fichier binaire llama.cpp a été téléchargé et extrait dans {0}\nLes fichiers CUDA ont été extraits dans {1}" self.CUDA_FILES_EXTRACTED = "Les fichiers CUDA ont été extraits dans" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "Aucun backend CUDA approprié trouvé pour l'extraction" ) self.ERROR_FETCHING_RELEASES = ( "Erreur lors de la récupération des versions : {0}" # Spacing ) self.CONFIRM_DELETION_TITLE = "Confirmer la suppression" self.LOG_FOR = "Journal pour {0}" self.ALL_FILES = "Tous les fichiers (*)" self.GGUF_FILES = "Fichiers GGUF (*.gguf)" self.DAT_FILES = "Fichiers DAT (*.dat)" self.JSON_FILES = "Fichiers JSON (*.json)" self.FAILED_LOAD_PRESET = "Échec du chargement du préréglage : {0}" # Spacing self.INITIALIZING_AUTOGGUF = "Initialisation de l'application AutoGGUF" self.AUTOGGUF_INITIALIZATION_COMPLETE = "Initialisation d'AutoGGUF terminée" self.REFRESHING_BACKENDS = "Actualisation des moteurs d'arrière-plan" self.NO_BACKENDS_AVAILABLE = "Aucun moteur d'arrière-plan disponible" self.FOUND_VALID_BACKENDS = "{0} moteurs d'arrière-plan valides trouvés" self.SAVING_PRESET = "Enregistrement du préréglage" self.PRESET_SAVED_TO = "Préréglage enregistré dans {0}" self.LOADING_PRESET = "Chargement du préréglage" self.PRESET_LOADED_FROM = "Préréglage chargé depuis {0}" self.ADDING_KV_OVERRIDE = "Ajout de remplacement KV : {0}" # Spacing self.SAVING_TASK_PRESET = "Enregistrement du préréglage de tâche pour {0}" self.TASK_PRESET_SAVED = "Préréglage de tâche enregistré" self.TASK_PRESET_SAVED_TO = "Préréglage de tâche enregistré dans {0}" self.RESTARTING_TASK = "Redémarrage de la tâche : {0}" # Spacing self.IN_PROGRESS = "En cours" self.DOWNLOAD_FINISHED_EXTRACTED_TO = ( "Téléchargement terminé. Extrait dans : {0}" # Spacing ) self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "Le fichier binaire llama.cpp a été téléchargé et extrait dans {0}\nLes fichiers CUDA ont été extraits dans {1}" self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "Aucun backend CUDA approprié trouvé pour l'extraction" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "Le fichier binaire llama.cpp a été téléchargé et extrait dans {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "Actualisation des versions de llama.cpp" self.UPDATING_ASSET_LIST = "Mise à jour de la liste des actifs" self.UPDATING_CUDA_OPTIONS = "Mise à jour des options CUDA" self.STARTING_LLAMACPP_DOWNLOAD = "Démarrage du téléchargement de llama.cpp" self.UPDATING_CUDA_BACKENDS = "Mise à jour des backends CUDA" self.NO_CUDA_BACKEND_SELECTED = ( "Aucun backend CUDA sélectionné pour l'extraction" ) self.EXTRACTING_CUDA_FILES = "Extraction des fichiers CUDA de {0} à {1}" self.DOWNLOAD_ERROR = "Erreur de téléchargement : {0}" # Spacing self.SHOWING_TASK_CONTEXT_MENU = "Affichage du menu contextuel de la tâche" self.SHOWING_PROPERTIES_FOR_TASK = ( "Affichage des propriétés de la tâche : {0}" # Spacing ) self.CANCELLING_TASK = "Annulation de la tâche : {0}" # Spacing self.CANCELED = "Annulée" self.DELETING_TASK = "Suppression de la tâche : {0}" # Spacing self.LOADING_MODELS = "Chargement des modèles" self.LOADED_MODELS = "{0} modèles chargés" self.BROWSING_FOR_MODELS_DIRECTORY = "Navigation dans le répertoire des modèles" self.SELECT_MODELS_DIRECTORY = "Sélectionner le répertoire des modèles" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Navigation dans le répertoire de sortie" self.SELECT_OUTPUT_DIRECTORY = "Sélectionner le répertoire de sortie" self.BROWSING_FOR_LOGS_DIRECTORY = "Navigation dans le répertoire des journaux" self.SELECT_LOGS_DIRECTORY = "Sélectionner le répertoire des journaux" self.BROWSING_FOR_IMATRIX_FILE = "Navigation dans le fichier IMatrix" self.SELECT_IMATRIX_FILE = "Sélectionner le fichier IMatrix" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} Mo / {2} Mo)" self.CPU_USAGE_FORMAT = "Utilisation du CPU : {0:.1f}%" # Spacing self.VALIDATING_QUANTIZATION_INPUTS = "Validation des entrées de quantification" self.MODELS_PATH_REQUIRED = "Le chemin des modèles est requis" self.OUTPUT_PATH_REQUIRED = "Le chemin de sortie est requis" self.LOGS_PATH_REQUIRED = "Le chemin des journaux est requis" self.STARTING_MODEL_QUANTIZATION = "Démarrage de la quantification du modèle" self.INPUT_FILE_NOT_EXIST = "Le fichier d'entrée '{0}' n'existe pas." self.QUANTIZING_MODEL_TO = "Quantification de {0} en {1}" self.QUANTIZATION_TASK_STARTED = "Tâche de quantification démarrée pour {0}" self.ERROR_STARTING_QUANTIZATION = ( "Erreur lors du démarrage de la quantification : {0}" # Spacing ) self.UPDATING_MODEL_INFO = ( "Mise à jour des informations sur le modèle : {0}" # Spacing ) self.TASK_FINISHED = "Tâche terminée : {0}" # Spacing self.SHOWING_TASK_DETAILS_FOR = ( "Affichage des détails de la tâche pour : {0}" # Spacing ) self.BROWSING_FOR_IMATRIX_DATA_FILE = ( "Navigation dans le fichier de données IMatrix" ) self.SELECT_DATA_FILE = "Sélectionner le fichier de données" self.BROWSING_FOR_IMATRIX_MODEL_FILE = ( "Navigation dans le fichier de modèle IMatrix" ) self.SELECT_MODEL_FILE = "Sélectionner le fichier de modèle" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = ( "Navigation dans le fichier de sortie IMatrix" ) self.SELECT_OUTPUT_FILE = "Sélectionner le fichier de sortie" self.STARTING_IMATRIX_GENERATION = "Démarrage de la génération d'IMatrix" self.BACKEND_PATH_NOT_EXIST = ( "Le chemin du backend n'existe pas : {0}" # Spacing ) self.GENERATING_IMATRIX = "Génération d'IMatrix" self.ERROR_STARTING_IMATRIX_GENERATION = ( "Erreur lors du démarrage de la génération d'IMatrix : {0}" # Spacing ) self.IMATRIX_GENERATION_TASK_STARTED = "Tâche de génération d'IMatrix démarrée" self.ERROR_MESSAGE = "Erreur : {0}" # Spacing self.TASK_ERROR = "Erreur de tâche : {0}" # Spacing self.APPLICATION_CLOSING = "Fermeture de l'application" self.APPLICATION_CLOSED = "Application fermée" self.SELECT_QUANTIZATION_TYPE = "Sélectionnez le type de quantification" self.ALLOWS_REQUANTIZING = ( "Permet de requantifier les tenseurs qui ont déjà été quantifiés" ) self.LEAVE_OUTPUT_WEIGHT = "Laissera output.weight non (re)quantifié" self.DISABLE_K_QUANT_MIXTURES = "Désactiver les mélanges k-quant et quantifier tous les tenseurs du même type" self.USE_DATA_AS_IMPORTANCE_MATRIX = "Utiliser les données du fichier comme matrice d'importance pour les optimisations de quant" self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Utiliser la matrice d'importance pour ces tenseurs" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Ne pas utiliser la matrice d'importance pour ces tenseurs" ) self.OUTPUT_TENSOR_TYPE = "Type de tenseur de sortie :" # Spacing self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Utiliser ce type pour le tenseur output.weight" ) self.TOKEN_EMBEDDING_TYPE = "Type d'intégration de jeton :" # Spacing self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Utiliser ce type pour le tenseur d'intégration de jetons" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "Générera le modèle quantifié dans les mêmes fragments que l'entrée" ) self.OVERRIDE_MODEL_METADATA = "Remplacer les métadonnées du modèle" self.INPUT_DATA_FILE_FOR_IMATRIX = ( "Fichier de données d'entrée pour la génération d'IMatrix" ) self.MODEL_TO_BE_QUANTIZED = "Modèle à quantifier" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = ( "Chemin de sortie pour l'IMatrix généré" ) self.HOW_OFTEN_TO_SAVE_IMATRIX = "Fréquence d'enregistrement de l'IMatrix" self.SET_GPU_OFFLOAD_VALUE = "Définir la valeur de déchargement GPU (-ngl)" self.COMPLETED = "Terminé" self.REFRESH_MODELS = "Rafraîchir les modèles" class _Portuguese_PT(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (Quantificador Automático de Modelos GGUF)" self.RAM_USAGE = "Utilização de RAM:" self.CPU_USAGE = "Utilização da CPU:" self.BACKEND = "Backend Llama.cpp:" self.REFRESH_BACKENDS = "Atualizar Backends" self.MODELS_PATH = "Caminho dos Modelos:" self.OUTPUT_PATH = "Caminho de Saída:" self.LOGS_PATH = "Caminho dos Logs:" self.BROWSE = "Navegar" self.AVAILABLE_MODELS = "Modelos Disponíveis:" self.QUANTIZATION_TYPE = "Tipo de Quantização:" self.ALLOW_REQUANTIZE = "Permitir Requantização" self.LEAVE_OUTPUT_TENSOR = "Manter Tensor de Saída" self.PURE = "Puro" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "Incluir Pesos:" self.EXCLUDE_WEIGHTS = "Excluir Pesos:" self.USE_OUTPUT_TENSOR_TYPE = "Usar Tipo de Tensor de Saída" self.USE_TOKEN_EMBEDDING_TYPE = "Usar Tipo de Incorporação de Token" self.KEEP_SPLIT = "Manter Divisão" self.KV_OVERRIDES = "Substituições KV:" self.ADD_NEW_OVERRIDE = "Adicionar Nova Substituição" self.QUANTIZE_MODEL = "Quantizar Modelo" self.SAVE_PRESET = "Guardar Predefinição" self.LOAD_PRESET = "Carregar Predefinição" self.TASKS = "Tarefas:" self.DOWNLOAD_LLAMACPP = "Descarregar llama.cpp" self.SELECT_RELEASE = "Selecionar Versão:" self.SELECT_ASSET = "Selecionar Ativo:" self.EXTRACT_CUDA_FILES = "Extrair Ficheiros CUDA" self.SELECT_CUDA_BACKEND = "Selecionar Backend CUDA:" self.DOWNLOAD = "Descarregar" self.IMATRIX_GENERATION = "Geração de IMatrix" self.DATA_FILE = "Ficheiro de Dados:" self.MODEL = "Modelo:" self.OUTPUT = "Saída:" self.OUTPUT_FREQUENCY = "Frequência de Saída:" self.GPU_OFFLOAD = "Offload da GPU:" self.AUTO = "Automático" self.GENERATE_IMATRIX = "Gerar IMatrix" self.ERROR = "Erro" self.WARNING = "Aviso" self.PROPERTIES = "Propriedades" self.CANCEL = "Cancelar" self.RESTART = "Reiniciar" self.DELETE = "Eliminar" self.CONFIRM_DELETION = "Tem a certeza de que pretende eliminar esta tarefa?" self.TASK_RUNNING_WARNING = "Algumas tarefas ainda estão em execução. Tem a certeza de que pretende sair?" self.YES = "Sim" self.NO = "Não" self.DOWNLOAD_COMPLETE = "Transferência Concluída" self.CUDA_EXTRACTION_FAILED = "Falha na Extração do CUDA" self.PRESET_SAVED = "Predefinição Guardada" self.PRESET_LOADED = "Predefinição Carregada" self.NO_ASSET_SELECTED = "Nenhum ativo selecionado" self.DOWNLOAD_FAILED = "Falha na transferência" self.NO_BACKEND_SELECTED = "Nenhum backend selecionado" self.NO_MODEL_SELECTED = "Nenhum modelo selecionado" self.REFRESH_RELEASES = "Atualizar Versões" self.NO_SUITABLE_CUDA_BACKENDS = "Nenhum backend CUDA adequado encontrado" self.LLAMACPP_DOWNLOADED_EXTRACTED = "Binário llama.cpp transferido e extraído para {0}\nFicheiros CUDA extraídos para {1}" self.CUDA_FILES_EXTRACTED = "Ficheiros CUDA extraídos para" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "Nenhum backend CUDA adequado encontrado para extração" ) self.ERROR_FETCHING_RELEASES = "Erro ao obter versões: {0}" self.CONFIRM_DELETION_TITLE = "Confirmar Eliminação" self.LOG_FOR = "Log para {0}" self.ALL_FILES = "Todos os Ficheiros (*)" self.GGUF_FILES = "Ficheiros GGUF (*.gguf)" self.DAT_FILES = "Ficheiros DAT (*.dat)" self.JSON_FILES = "Ficheiros JSON (*.json)" self.FAILED_LOAD_PRESET = "Falha ao carregar a predefinição: {0}" self.INITIALIZING_AUTOGGUF = "A inicializar a aplicação AutoGGUF" self.AUTOGGUF_INITIALIZATION_COMPLETE = "Inicialização do AutoGGUF concluída" self.REFRESHING_BACKENDS = "A atualizar backends" self.NO_BACKENDS_AVAILABLE = "Nenhum backend disponível" self.FOUND_VALID_BACKENDS = "{0} backends válidos encontrados" self.SAVING_PRESET = "A guardar predefinição" self.PRESET_SAVED_TO = "Predefinição guardada em {0}" self.LOADING_PRESET = "A carregar predefinição" self.PRESET_LOADED_FROM = "Predefinição carregada de {0}" self.ADDING_KV_OVERRIDE = "A adicionar substituição KV: {0}" self.SAVING_TASK_PRESET = "A guardar predefinição de tarefa para {0}" self.TASK_PRESET_SAVED = "Predefinição de Tarefa Guardada" self.TASK_PRESET_SAVED_TO = "Predefinição de tarefa guardada em {0}" self.RESTARTING_TASK = "A reiniciar tarefa: {0}" self.IN_PROGRESS = "Em Andamento" self.DOWNLOAD_FINISHED_EXTRACTED_TO = ( "Transferência concluída. Extraído para: {0}" ) self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "Binário llama.cpp transferido e extraído para {0}\nFicheiros CUDA extraídos para {1}" self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "Nenhum backend CUDA adequado encontrado para extração" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "Binário llama.cpp transferido e extraído para {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "A atualizar versões do llama.cpp" self.UPDATING_ASSET_LIST = "A atualizar lista de ativos" self.UPDATING_CUDA_OPTIONS = "A atualizar opções CUDA" self.STARTING_LLAMACPP_DOWNLOAD = "A iniciar transferência do llama.cpp" self.UPDATING_CUDA_BACKENDS = "A atualizar backends CUDA" self.NO_CUDA_BACKEND_SELECTED = "Nenhum backend CUDA selecionado para extração" self.EXTRACTING_CUDA_FILES = "A extrair ficheiros CUDA de {0} para {1}" self.DOWNLOAD_ERROR = "Erro de transferência: {0}" self.SHOWING_TASK_CONTEXT_MENU = "A exibir menu de contexto da tarefa" self.SHOWING_PROPERTIES_FOR_TASK = "A exibir propriedades para a tarefa: {0}" self.CANCELLING_TASK = "A cancelar tarefa: {0}" self.CANCELED = "Cancelado" self.DELETING_TASK = "A eliminar tarefa: {0}" self.LOADING_MODELS = "A carregar modelos" self.LOADED_MODELS = "{0} modelos carregados" self.BROWSING_FOR_MODELS_DIRECTORY = "A navegar pelo diretório de modelos" self.SELECT_MODELS_DIRECTORY = "Selecionar Diretório de Modelos" self.BROWSING_FOR_OUTPUT_DIRECTORY = "A navegar pelo diretório de saída" self.SELECT_OUTPUT_DIRECTORY = "Selecionar Diretório de Saída" self.BROWSING_FOR_LOGS_DIRECTORY = "A navegar pelo diretório de logs" self.SELECT_LOGS_DIRECTORY = "Selecionar Diretório de Logs" self.BROWSING_FOR_IMATRIX_FILE = "A navegar pelo ficheiro IMatrix" self.SELECT_IMATRIX_FILE = "Selecionar Ficheiro IMatrix" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "Utilização da CPU: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "A validar entradas de quantização" self.MODELS_PATH_REQUIRED = "O caminho dos modelos é obrigatório" self.OUTPUT_PATH_REQUIRED = "O caminho de saída é obrigatório" self.LOGS_PATH_REQUIRED = "O caminho dos logs é obrigatório" self.STARTING_MODEL_QUANTIZATION = "A iniciar a quantização do modelo" self.INPUT_FILE_NOT_EXIST = "O ficheiro de entrada '{0}' não existe." self.QUANTIZING_MODEL_TO = "A quantizar {0} para {1}" self.QUANTIZATION_TASK_STARTED = "Tarefa de quantização iniciada para {0}" self.ERROR_STARTING_QUANTIZATION = "Erro ao iniciar a quantização: {0}" self.UPDATING_MODEL_INFO = "A atualizar informações do modelo: {0}" self.TASK_FINISHED = "Tarefa concluída: {0}" self.SHOWING_TASK_DETAILS_FOR = "A mostrar detalhes da tarefa para: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "A navegar pelo ficheiro de dados IMatrix" self.SELECT_DATA_FILE = "Selecionar Ficheiro de Dados" self.BROWSING_FOR_IMATRIX_MODEL_FILE = ( "A navegar pelo ficheiro de modelo IMatrix" ) self.SELECT_MODEL_FILE = "Selecionar Ficheiro de Modelo" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = ( "A navegar pelo ficheiro de saída IMatrix" ) self.SELECT_OUTPUT_FILE = "Selecionar Ficheiro de Saída" self.STARTING_IMATRIX_GENERATION = "A iniciar a geração de IMatrix" self.BACKEND_PATH_NOT_EXIST = "O caminho do backend não existe: {0}" self.GENERATING_IMATRIX = "A gerar IMatrix" self.ERROR_STARTING_IMATRIX_GENERATION = ( "Erro ao iniciar a geração de IMatrix: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "Tarefa de geração de IMatrix iniciada" self.ERROR_MESSAGE = "Erro: {0}" self.TASK_ERROR = "Erro de tarefa: {0}" self.APPLICATION_CLOSING = "A fechar a aplicação" self.APPLICATION_CLOSED = "Aplicação fechada" self.SELECT_QUANTIZATION_TYPE = "Selecione o tipo de quantização" self.ALLOWS_REQUANTIZING = ( "Permite requantizar tensores que já foram quantizados" ) self.LEAVE_OUTPUT_WEIGHT = "Deixará output.weight não (re)quantizado" self.DISABLE_K_QUANT_MIXTURES = ( "Desativar misturas k-quant e quantizar todos os tensores para o mesmo tipo" ) self.USE_DATA_AS_IMPORTANCE_MATRIX = "Usar os dados no ficheiro como matriz de importância para otimizações de quantização" self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Usar matriz de importância para estes tensores" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Não usar matriz de importância para estes tensores" ) self.OUTPUT_TENSOR_TYPE = "Tipo de Tensor de Saída:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Usar este tipo para o tensor output.weight" ) self.TOKEN_EMBEDDING_TYPE = "Tipo de Incorporação de Token:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Usar este tipo para o tensor de incorporações de token" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "Irá gerar o modelo quantizado nos mesmos shards da entrada" ) self.OVERRIDE_MODEL_METADATA = "Substituir metadados do modelo" self.INPUT_DATA_FILE_FOR_IMATRIX = ( "Ficheiro de dados de entrada para geração de IMatrix" ) self.MODEL_TO_BE_QUANTIZED = "Modelo a ser quantizado" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = ( "Caminho de saída para o IMatrix gerado" ) self.HOW_OFTEN_TO_SAVE_IMATRIX = "Com que frequência guardar o IMatrix" self.SET_GPU_OFFLOAD_VALUE = "Definir valor de offload da GPU (-ngl)" self.COMPLETED = "Concluído" self.REFRESH_MODELS = "Atualizar modelos" class _Greek(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (Αυτόματος Κβαντιστής Μοντέλων GGUF)" self.RAM_USAGE = "Χρήση RAM:" self.CPU_USAGE = "Χρήση CPU:" self.BACKEND = "Backend Llama.cpp:" self.REFRESH_BACKENDS = "Ανανέωση Backends" self.MODELS_PATH = "Διαδρομή Μοντέλων:" self.OUTPUT_PATH = "Διαδρομή Εξόδου:" self.LOGS_PATH = "Διαδρομή Αρχείων Καταγραφής:" self.BROWSE = "Περιήγηση" self.AVAILABLE_MODELS = "Διαθέσιμα Μοντέλα:" self.QUANTIZATION_TYPE = "Τύπος Κβαντισμού:" self.ALLOW_REQUANTIZE = "Να Επιτρέπεται η Επανακβάντιση" self.LEAVE_OUTPUT_TENSOR = "Διατήρηση Tensor Εξόδου" self.PURE = "Καθαρό" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "Συμπερίληψη Βαρών:" self.EXCLUDE_WEIGHTS = "Εξαίρεση Βαρών:" self.USE_OUTPUT_TENSOR_TYPE = "Χρήση Τύπου Tensor Εξόδου" self.USE_TOKEN_EMBEDDING_TYPE = "Χρήση Τύπου Ενσωμάτωσης Token" self.KEEP_SPLIT = "Διατήρηση Διαίρεσης" self.KV_OVERRIDES = "Υπερβάσεις KV:" self.ADD_NEW_OVERRIDE = "Προσθήκη Νέας Υπέρβασης" self.QUANTIZE_MODEL = "Κβάντιση Μοντέλου" self.SAVE_PRESET = "Αποθήκευση Προεπιλογής" self.LOAD_PRESET = "Φόρτωση Προεπιλογής" self.TASKS = "Εργασίες:" self.DOWNLOAD_LLAMACPP = "Λήψη llama.cpp" self.SELECT_RELEASE = "Επιλογή Έκδοσης:" self.SELECT_ASSET = "Επιλογή Στοιχείου:" self.EXTRACT_CUDA_FILES = "Εξαγωγή Αρχείων CUDA" self.SELECT_CUDA_BACKEND = "Επιλογή Backend CUDA:" self.DOWNLOAD = "Λήψη" self.IMATRIX_GENERATION = "Δημιουργία IMatrix" self.DATA_FILE = "Αρχείο Δεδομένων:" self.MODEL = "Μοντέλο:" self.OUTPUT = "Έξοδος:" self.OUTPUT_FREQUENCY = "Συχνότητα Εξόδου:" self.GPU_OFFLOAD = "Εκφόρτωση GPU:" self.AUTO = "Αυτόματο" self.GENERATE_IMATRIX = "Δημιουργία IMatrix" self.ERROR = "Σφάλμα" self.WARNING = "Προειδοποίηση" self.PROPERTIES = "Ιδιότητες" self.CANCEL = "Ακύρωση" self.RESTART = "Επανεκκίνηση" self.DELETE = "Διαγραφή" self.CONFIRM_DELETION = ( "Είστε βέβαιοι ότι θέλετε να διαγράψετε αυτήν την εργασία;" ) self.TASK_RUNNING_WARNING = "Ορισμένες εργασίες εκτελούνται ακόμη. Είστε βέβαιοι ότι θέλετε να τερματίσετε;" self.YES = "Ναι" self.NO = "Όχι" self.DOWNLOAD_COMPLETE = "Η Λήψη Ολοκληρώθηκε" self.CUDA_EXTRACTION_FAILED = "Αποτυχία Εξαγωγής CUDA" self.PRESET_SAVED = "Η Προεπιλογή Αποθηκεύτηκε" self.PRESET_LOADED = "Η Προεπιλογή Φορτώθηκε" self.NO_ASSET_SELECTED = "Δεν Έχει Επιλεγεί Στοιχείο" self.DOWNLOAD_FAILED = "Αποτυχία Λήψης" self.NO_BACKEND_SELECTED = "Δεν Έχει Επιλεγεί Backend" self.NO_MODEL_SELECTED = "Δεν Έχει Επιλεγεί Μοντέλο" self.REFRESH_RELEASES = "Ανανέωση Εκδόσεων" self.NO_SUITABLE_CUDA_BACKENDS = "Δεν Βρέθηκαν Κατάλληλα Backends CUDA" self.LLAMACPP_DOWNLOADED_EXTRACTED = "Το Δυαδικό Αρχείο llama.cpp Λήφθηκε και Εξήχθη στο {0}\nΤα Αρχεία CUDA Εξήχθησαν στο {1}" self.CUDA_FILES_EXTRACTED = "Τα Αρχεία CUDA Εξήχθησαν στο" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "Δεν Βρέθηκε Κατάλληλο Backend CUDA για Εξαγωγή" ) self.ERROR_FETCHING_RELEASES = "Σφάλμα κατά την Ανάκτηση Εκδόσεων: {0}" self.CONFIRM_DELETION_TITLE = "Επιβεβαίωση Διαγραφής" self.LOG_FOR = "Αρχείο Καταγραφής για {0}" self.ALL_FILES = "Όλα τα Αρχεία (*)" self.GGUF_FILES = "Αρχεία GGUF (*.gguf)" self.DAT_FILES = "Αρχεία DAT (*.dat)" self.JSON_FILES = "Αρχεία JSON (*.json)" self.FAILED_LOAD_PRESET = "Αποτυχία Φόρτωσης Προεπιλογής: {0}" self.INITIALIZING_AUTOGGUF = "Εκκίνηση Εφαρμογής AutoGGUF" self.AUTOGGUF_INITIALIZATION_COMPLETE = "Η Εκκίνηση του AutoGGUF Ολοκληρώθηκε" self.REFRESHING_BACKENDS = "Ανανέωση Backends" self.NO_BACKENDS_AVAILABLE = "Δεν Υπάρχουν Διαθέσιμα Backends" self.FOUND_VALID_BACKENDS = "Βρέθηκαν {0} Έγκυρα Backends" self.SAVING_PRESET = "Αποθήκευση Προεπιλογής" self.PRESET_SAVED_TO = "Η Προεπιλογή Αποθηκεύτηκε στο {0}" self.LOADING_PRESET = "Φόρτωση Προεπιλογής" self.PRESET_LOADED_FROM = "Η Προεπιλογή Φορτώθηκε από το {0}" self.ADDING_KV_OVERRIDE = "Προσθήκη Υπέρβασης KV: {0}" self.SAVING_TASK_PRESET = "Αποθήκευση Προεπιλογής Εργασίας για {0}" self.TASK_PRESET_SAVED = "Η Προεπιλογή Εργασίας Αποθηκεύτηκε" self.TASK_PRESET_SAVED_TO = "Η Προεπιλογή Εργασίας Αποθηκεύτηκε στο {0}" self.RESTARTING_TASK = "Επανεκκίνηση Εργασίας: {0}" self.IN_PROGRESS = "Σε Εξέλιξη" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "Η Λήψη Ολοκληρώθηκε. Εξήχθη στο: {0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "Το Δυαδικό Αρχείο llama.cpp Λήφθηκε και Εξήχθη στο {0}\nΤα Αρχεία CUDA Εξήχθησαν στο {1}" self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "Δεν Βρέθηκε Κατάλληλο Backend CUDA για Εξαγωγή" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "Το Δυαδικό Αρχείο llama.cpp Λήφθηκε και Εξήχθη στο {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "Ανανέωση Εκδόσεων llama.cpp" self.UPDATING_ASSET_LIST = "Ενημέρωση Λίστας Στοιχείων" self.UPDATING_CUDA_OPTIONS = "Ενημέρωση Επιλογών CUDA" self.STARTING_LLAMACPP_DOWNLOAD = "Έναρξη Λήψης llama.cpp" self.UPDATING_CUDA_BACKENDS = "Ενημέρωση Backends CUDA" self.NO_CUDA_BACKEND_SELECTED = "Δεν Έχει Επιλεγεί Backend CUDA για Εξαγωγή" self.EXTRACTING_CUDA_FILES = "Εξαγωγή Αρχείων CUDA από {0} στο {1}" self.DOWNLOAD_ERROR = "Σφάλμα Λήψης: {0}" self.SHOWING_TASK_CONTEXT_MENU = "Εμφάνιση Μενού Περιεχομένου Εργασίας" self.SHOWING_PROPERTIES_FOR_TASK = "Εμφάνιση Ιδιοτήτων για την Εργασία: {0}" self.CANCELLING_TASK = "Ακύρωση Εργασίας: {0}" self.CANCELED = "Ακυρώθηκε" self.DELETING_TASK = "Διαγραφή Εργασίας: {0}" self.LOADING_MODELS = "Φόρτωση Μοντέλων" self.LOADED_MODELS = "{0} Μοντέλα Φορτώθηκαν" self.BROWSING_FOR_MODELS_DIRECTORY = "Περιήγηση σε Φάκελο Μοντέλων" self.SELECT_MODELS_DIRECTORY = "Επιλέξτε Φάκελο Μοντέλων" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Περιήγηση σε Φάκελο Εξόδου" self.SELECT_OUTPUT_DIRECTORY = "Επιλέξτε Φάκελο Εξόδου" self.BROWSING_FOR_LOGS_DIRECTORY = "Περιήγηση σε Φάκελο Αρχείων Καταγραφής" self.SELECT_LOGS_DIRECTORY = "Επιλέξτε Φάκελο Αρχείων Καταγραφής" self.BROWSING_FOR_IMATRIX_FILE = "Περιήγηση σε Αρχείο IMatrix" self.SELECT_IMATRIX_FILE = "Επιλέξτε Αρχείο IMatrix" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "Χρήση CPU: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "Επικύρωση Εισόδων Κβαντισμού" self.MODELS_PATH_REQUIRED = "Απαιτείται η Διαδρομή Μοντέλων" self.OUTPUT_PATH_REQUIRED = "Απαιτείται η Διαδρομή Εξόδου" self.LOGS_PATH_REQUIRED = "Απαιτείται η Διαδρομή Αρχείων Καταγραφής" self.STARTING_MODEL_QUANTIZATION = "Έναρξη Κβαντισμού Μοντέλου" self.INPUT_FILE_NOT_EXIST = "Το Αρχείο Εισόδου '{0}' Δεν Υπάρχει." self.QUANTIZING_MODEL_TO = "Κβάντιση του {0} σε {1}" self.QUANTIZATION_TASK_STARTED = "Η Εργασία Κβαντισμού Ξεκίνησε για {0}" self.ERROR_STARTING_QUANTIZATION = "Σφάλμα κατά την Έναρξη Κβαντισμού: {0}" self.UPDATING_MODEL_INFO = "Ενημέρωση Πληροφοριών Μοντέλου: {0}" self.TASK_FINISHED = "Η Εργασία Ολοκληρώθηκε: {0}" self.SHOWING_TASK_DETAILS_FOR = "Εμφάνιση Λεπτομερειών Εργασίας για: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "Περιήγηση σε Αρχείο Δεδομένων IMatrix" self.SELECT_DATA_FILE = "Επιλέξτε Αρχείο Δεδομένων" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "Περιήγηση σε Αρχείο Μοντέλου IMatrix" self.SELECT_MODEL_FILE = "Επιλέξτε Αρχείο Μοντέλου" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "Περιήγηση σε Αρχείο Εξόδου IMatrix" self.SELECT_OUTPUT_FILE = "Επιλέξτε Αρχείο Εξόδου" self.STARTING_IMATRIX_GENERATION = "Έναρξη Δημιουργίας IMatrix" self.BACKEND_PATH_NOT_EXIST = "Η Διαδρομή Backend Δεν Υπάρχει: {0}" self.GENERATING_IMATRIX = "Δημιουργία IMatrix" self.ERROR_STARTING_IMATRIX_GENERATION = ( "Σφάλμα κατά την Έναρξη Δημιουργίας IMatrix: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "Η Εργασία Δημιουργίας IMatrix Ξεκίνησε" self.ERROR_MESSAGE = "Σφάλμα: {0}" self.TASK_ERROR = "Σφάλμα Εργασίας: {0}" self.APPLICATION_CLOSING = "Κλείσιμο Εφαρμογής" self.APPLICATION_CLOSED = "Η Εφαρμογή Έκλεισε" self.SELECT_QUANTIZATION_TYPE = "Επιλέξτε τον τύπο κβαντισμού" self.ALLOWS_REQUANTIZING = ( "Επιτρέπει την επανακβάντιση τανυστών που έχουν ήδη κβαντιστεί" ) self.LEAVE_OUTPUT_WEIGHT = "Θα αφήσει το output.weight χωρίς (επανα)κβάντιση" self.DISABLE_K_QUANT_MIXTURES = "Απενεργοποιήστε τα μείγματα k-quant και κβαντίστε όλους τους τανυστές στον ίδιο τύπο" self.USE_DATA_AS_IMPORTANCE_MATRIX = "Χρησιμοποιήστε τα δεδομένα στο αρχείο ως πίνακα σημασίας για βελτιστοποιήσεις κβαντισμού" self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Χρησιμοποιήστε τον πίνακα σημασίας για αυτούς τους τανυστές" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Μην χρησιμοποιείτε τον πίνακα σημασίας για αυτούς τους τανυστές" ) self.OUTPUT_TENSOR_TYPE = "Τύπος Tensor Εξόδου:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Χρησιμοποιήστε αυτόν τον τύπο για τον τανυστή output.weight" ) self.TOKEN_EMBEDDING_TYPE = "Τύπος Ενσωμάτωσης Token:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Χρησιμοποιήστε αυτόν τον τύπο για τον τανυστή ενσωματώσεων token" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "Θα δημιουργήσει το κβαντισμένο μοντέλο στα ίδια θραύσματα με την είσοδο" ) self.OVERRIDE_MODEL_METADATA = "Αντικατάσταση μεταδεδομένων μοντέλου" self.INPUT_DATA_FILE_FOR_IMATRIX = ( "Αρχείο δεδομένων εισόδου για τη δημιουργία IMatrix" ) self.MODEL_TO_BE_QUANTIZED = "Μοντέλο προς κβάντιση" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = ( "Διαδρομή εξόδου για το δημιουργημένο IMatrix" ) self.HOW_OFTEN_TO_SAVE_IMATRIX = "Πόσο συχνά να αποθηκεύεται το IMatrix" self.SET_GPU_OFFLOAD_VALUE = "Ορίστε την τιμή εκφόρτωσης GPU (-ngl)" self.COMPLETED = "Ολοκληρώθηκε" self.REFRESH_MODELS = "Ανανέωση μοντέλων" class _Hungarian(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (Automatizált GGUF modell kvantáló)" self.RAM_USAGE = "RAM használat:" self.CPU_USAGE = "CPU használat:" self.BACKEND = "Llama.cpp háttérrendszer:" self.REFRESH_BACKENDS = "Háttérrendszerek frissítése" self.MODELS_PATH = "Modellek elérési útja:" self.OUTPUT_PATH = "Kimeneti útvonal:" self.LOGS_PATH = "Naplók elérési útja:" self.BROWSE = "Tallózás" self.AVAILABLE_MODELS = "Elérhető modellek:" self.QUANTIZATION_TYPE = "Kvantálási típus:" self.ALLOW_REQUANTIZE = "Újrakvantálás engedélyezése" self.LEAVE_OUTPUT_TENSOR = "Kimeneti tenzor meghagyása" self.PURE = "Tiszta" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "Súlyok belefoglalása:" self.EXCLUDE_WEIGHTS = "Súlyok kizárása:" self.USE_OUTPUT_TENSOR_TYPE = "Kimeneti tenzor típusának használata" self.USE_TOKEN_EMBEDDING_TYPE = "Token beágyazási típusának használata" self.KEEP_SPLIT = "Felosztás megtartása" self.KV_OVERRIDES = "KV felülbírálások:" self.ADD_NEW_OVERRIDE = "Új felülbírálás hozzáadása" self.QUANTIZE_MODEL = "Modell kvantálása" self.SAVE_PRESET = "Esetbeállítás mentése" self.LOAD_PRESET = "Esetbeállítás betöltése" self.TASKS = "Feladatok:" self.DOWNLOAD_LLAMACPP = "llama.cpp letöltése" self.SELECT_RELEASE = "Kiadás kiválasztása:" self.SELECT_ASSET = "Eszköz kiválasztása:" self.EXTRACT_CUDA_FILES = "CUDA fájlok kibontása" self.SELECT_CUDA_BACKEND = "CUDA háttérrendszer kiválasztása:" self.DOWNLOAD = "Letöltés" self.IMATRIX_GENERATION = "IMatrix generálás" self.DATA_FILE = "Adatfájl:" self.MODEL = "Modell:" self.OUTPUT = "Kimenet:" self.OUTPUT_FREQUENCY = "Kimeneti frekvencia:" self.GPU_OFFLOAD = "GPU tehermentesítés:" self.AUTO = "Automatikus" self.GENERATE_IMATRIX = "IMatrix generálása" self.ERROR = "Hiba" self.WARNING = "Figyelmeztetés" self.PROPERTIES = "Tulajdonságok" self.CANCEL = "Mégse" self.RESTART = "Újraindítás" self.DELETE = "Törlés" self.CONFIRM_DELETION = "Biztosan törölni szeretné ezt a feladatot?" self.TASK_RUNNING_WARNING = "Néhány feladat még fut. Biztosan kilép?" self.YES = "Igen" self.NO = "Nem" self.DOWNLOAD_COMPLETE = "Letöltés befejeződött" self.CUDA_EXTRACTION_FAILED = "CUDA kibontás sikertelen" self.PRESET_SAVED = "Esetbeállítás mentve" self.PRESET_LOADED = "Esetbeállítás betöltve" self.NO_ASSET_SELECTED = "Nincs kiválasztott eszköz" self.DOWNLOAD_FAILED = "Letöltés sikertelen" self.NO_BACKEND_SELECTED = "Nincs kiválasztott háttérrendszer" self.NO_MODEL_SELECTED = "Nincs kiválasztott modell" self.REFRESH_RELEASES = "Kiadások frissítése" self.NO_SUITABLE_CUDA_BACKENDS = "Nem található megfelelő CUDA háttérrendszer" self.LLAMACPP_DOWNLOADED_EXTRACTED = "A llama.cpp bináris fájl letöltve és kibontva ide: {0}\nA CUDA fájlok kibontva ide: {1}" self.CUDA_FILES_EXTRACTED = "A CUDA fájlok kibontva ide:" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "Nem található megfelelő CUDA háttérrendszer a kibontáshoz" ) self.ERROR_FETCHING_RELEASES = "Hiba a kiadások lekérdezésekor: {0}" self.CONFIRM_DELETION_TITLE = "Törlés megerősítése" self.LOG_FOR = "Napló a következőhöz: {0}" self.ALL_FILES = "Minden fájl (*)" self.GGUF_FILES = "GGUF fájlok (*.gguf)" self.DAT_FILES = "DAT fájlok (*.dat)" self.JSON_FILES = "JSON fájlok (*.json)" self.FAILED_LOAD_PRESET = "Az esetbeállítás betöltése sikertelen: {0}" self.INITIALIZING_AUTOGGUF = "Az AutoGGUF alkalmazás inicializálása" self.AUTOGGUF_INITIALIZATION_COMPLETE = ( "Az AutoGGUF inicializálása befejeződött" ) self.REFRESHING_BACKENDS = "Háttérrendszerek frissítése" self.NO_BACKENDS_AVAILABLE = "Nincsenek elérhető háttérrendszerek" self.FOUND_VALID_BACKENDS = "{0} érvényes háttérrendszer található" self.SAVING_PRESET = "Esetbeállítás mentése" self.PRESET_SAVED_TO = "Esetbeállítás mentve ide: {0}" self.LOADING_PRESET = "Esetbeállítás betöltése" self.PRESET_LOADED_FROM = "Esetbeállítás betöltve innen: {0}" self.ADDING_KV_OVERRIDE = "KV felülbírálás hozzáadása: {0}" self.SAVING_TASK_PRESET = "Feladat esetbeállítás mentése ehhez: {0}" self.TASK_PRESET_SAVED = "Feladat esetbeállítás mentve" self.TASK_PRESET_SAVED_TO = "Feladat esetbeállítás mentve ide: {0}" self.RESTARTING_TASK = "Feladat újraindítása: {0}" self.IN_PROGRESS = "Folyamatban" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "Letöltés befejeződött. Kibontva ide: {0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "A llama.cpp bináris fájl letöltve és kibontva ide: {0}\nA CUDA fájlok kibontva ide: {1}" self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "Nem található megfelelő CUDA háttérrendszer a kibontáshoz" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "A llama.cpp bináris fájl letöltve és kibontva ide: {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "A llama.cpp kiadások frissítése" self.UPDATING_ASSET_LIST = "Eszközlista frissítése" self.UPDATING_CUDA_OPTIONS = "CUDA beállítások frissítése" self.STARTING_LLAMACPP_DOWNLOAD = "A llama.cpp letöltésének megkezdése" self.UPDATING_CUDA_BACKENDS = "CUDA háttérrendszerek frissítése" self.NO_CUDA_BACKEND_SELECTED = ( "Nincs kiválasztott CUDA háttérrendszer a kibontáshoz" ) self.EXTRACTING_CUDA_FILES = "CUDA fájlok kibontása innen: {0} ide: {1}" self.DOWNLOAD_ERROR = "Letöltési hiba: {0}" self.SHOWING_TASK_CONTEXT_MENU = "Feladat helyi menüjének megjelenítése" self.SHOWING_PROPERTIES_FOR_TASK = "Feladat tulajdonságainak megjelenítése: {0}" self.CANCELLING_TASK = "Feladat megszakítása: {0}" self.CANCELED = "Megszakítva" self.DELETING_TASK = "Feladat törlése: {0}" self.LOADING_MODELS = "Modellek betöltése" self.LOADED_MODELS = "{0} modell betöltve" self.BROWSING_FOR_MODELS_DIRECTORY = "Modellek könyvtárának tallózása" self.SELECT_MODELS_DIRECTORY = "Modellek könyvtárának kiválasztása" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Kimeneti könyvtár tallózása" self.SELECT_OUTPUT_DIRECTORY = "Kimeneti könyvtár kiválasztása" self.BROWSING_FOR_LOGS_DIRECTORY = "Naplók könyvtárának tallózása" self.SELECT_LOGS_DIRECTORY = "Naplók könyvtárának kiválasztása" self.BROWSING_FOR_IMATRIX_FILE = "IMatrix fájl tallózása" self.SELECT_IMATRIX_FILE = "IMatrix fájl kiválasztása" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "CPU használat: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "Kvantálási bemenetek ellenőrzése" self.MODELS_PATH_REQUIRED = "A modellek elérési útja kötelező" self.OUTPUT_PATH_REQUIRED = "A kimeneti útvonal kötelező" self.LOGS_PATH_REQUIRED = "A naplók elérési útja kötelező" self.STARTING_MODEL_QUANTIZATION = "Modell kvantálásának indítása" self.INPUT_FILE_NOT_EXIST = "A bemeneti fájl '{0}' nem létezik." self.QUANTIZING_MODEL_TO = "{0} kvantálása erre: {1}" self.QUANTIZATION_TASK_STARTED = "Kvantálási feladat elindítva ehhez: {0}" self.ERROR_STARTING_QUANTIZATION = "Hiba a kvantálás indításakor: {0}" self.UPDATING_MODEL_INFO = "Modellinformációk frissítése: {0}" self.TASK_FINISHED = "Feladat befejezve: {0}" self.SHOWING_TASK_DETAILS_FOR = "Feladat részleteinek megjelenítése ehhez: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "IMatrix adatfájl tallózása" self.SELECT_DATA_FILE = "Adatfájl kiválasztása" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "IMatrix modellfájl tallózása" self.SELECT_MODEL_FILE = "Modellfájl kiválasztása" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "IMatrix kimeneti fájl tallózása" self.SELECT_OUTPUT_FILE = "Kimeneti fájl kiválasztása" self.STARTING_IMATRIX_GENERATION = "IMatrix generálásának indítása" self.BACKEND_PATH_NOT_EXIST = "A háttérrendszer elérési útja nem létezik: {0}" self.GENERATING_IMATRIX = "IMatrix generálása" self.ERROR_STARTING_IMATRIX_GENERATION = ( "Hiba az IMatrix generálásának indításakor: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "IMatrix generálási feladat elindítva" self.ERROR_MESSAGE = "Hiba: {0}" self.TASK_ERROR = "Feladat hiba: {0}" self.APPLICATION_CLOSING = "Alkalmazás bezárása" self.APPLICATION_CLOSED = "Alkalmazás bezárva" self.SELECT_QUANTIZATION_TYPE = "Válassza ki a kvantálási típust" self.ALLOWS_REQUANTIZING = ( "Lehetővé teszi a már kvantált tenzorok újrakvantálását" ) self.LEAVE_OUTPUT_WEIGHT = "Az output.weight-et (újra)kvantálatlanul hagyja" self.DISABLE_K_QUANT_MIXTURES = "Tiltsa le a k-kvant keverékeket, és kvantálja az összes tenzort ugyanarra a típusra" self.USE_DATA_AS_IMPORTANCE_MATRIX = "Használja a fájlban lévő adatokat fontossági mátrixként a kvantálási optimalizálásokhoz" self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Használja a fontossági mátrixot ezekre a tenzorokra" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Ne használja a fontossági mátrixot ezekre a tenzorokra" ) self.OUTPUT_TENSOR_TYPE = "Kimeneti tenzor típusa:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Használja ezt a típust az output.weight tenzorhoz" ) self.TOKEN_EMBEDDING_TYPE = "Token beágyazási típusa:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Használja ezt a típust a token beágyazási tenzorhoz" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = "A kvantált modellt ugyanazokban a szegmensekben fogja generálni, mint a bemenet" self.OVERRIDE_MODEL_METADATA = "Modell metaadatok felülbírálása" self.INPUT_DATA_FILE_FOR_IMATRIX = "IMatrix generáláshoz bemeneti adatfájl" self.MODEL_TO_BE_QUANTIZED = "Kvantálandó modell" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = "A generált IMatrix kimeneti útvonala" self.HOW_OFTEN_TO_SAVE_IMATRIX = "Milyen gyakran mentse az IMatrixot" self.SET_GPU_OFFLOAD_VALUE = "GPU tehermentesítési érték beállítása (-ngl)" self.COMPLETED = "Befejezve" self.REFRESH_MODELS = "Modellek frissítése" class _BritishEnglish(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (automated GGUF model quantiser)" self.RAM_USAGE = "RAM Usage:" self.CPU_USAGE = "CPU Usage:" self.BACKEND = "Llama.cpp Backend:" self.REFRESH_BACKENDS = "Refresh Backends" self.MODELS_PATH = "Models Path:" self.OUTPUT_PATH = "Output Path:" self.LOGS_PATH = "Logs Path:" self.BROWSE = "Browse" self.AVAILABLE_MODELS = "Available Models:" self.QUANTIZATION_TYPE = "Quantisation Type:" # Note the British spelling self.ALLOW_REQUANTIZE = "Allow Requantise" self.LEAVE_OUTPUT_TENSOR = "Leave Output Tensor" self.PURE = "Pure" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "Include Weights:" self.EXCLUDE_WEIGHTS = "Exclude Weights:" self.USE_OUTPUT_TENSOR_TYPE = "Use Output Tensor Type" self.USE_TOKEN_EMBEDDING_TYPE = "Use Token Embedding Type" self.KEEP_SPLIT = "Keep Split" self.KV_OVERRIDES = "KV Overrides:" self.ADD_NEW_OVERRIDE = "Add new override" self.QUANTIZE_MODEL = "Quantise Model" # Note the British spelling self.SAVE_PRESET = "Save Preset" self.LOAD_PRESET = "Load Preset" self.TASKS = "Tasks:" self.DOWNLOAD_LLAMACPP = "Download llama.cpp" self.SELECT_RELEASE = "Select Release:" self.SELECT_ASSET = "Select Asset:" self.EXTRACT_CUDA_FILES = "Extract CUDA files" self.SELECT_CUDA_BACKEND = "Select CUDA Backend:" self.DOWNLOAD = "Download" self.IMATRIX_GENERATION = "IMatrix Generation" self.DATA_FILE = "Data File:" self.MODEL = "Model:" self.OUTPUT = "Output:" self.OUTPUT_FREQUENCY = "Output Frequency:" self.GPU_OFFLOAD = "GPU Offload:" self.AUTO = "Auto" self.GENERATE_IMATRIX = "Generate IMatrix" self.ERROR = "Error" self.WARNING = "Warning" self.PROPERTIES = "Properties" self.CANCEL = "Cancel" self.RESTART = "Restart" self.DELETE = "Delete" self.CONFIRM_DELETION = "Are you sure you want to delete this task?" self.TASK_RUNNING_WARNING = ( "Some tasks are still running. Are you sure you want to quit?" ) self.YES = "Yes" self.NO = "No" self.DOWNLOAD_COMPLETE = "Download Complete" self.CUDA_EXTRACTION_FAILED = "CUDA Extraction Failed" self.PRESET_SAVED = "Preset Saved" self.PRESET_LOADED = "Preset Loaded" self.NO_ASSET_SELECTED = "No asset selected" self.DOWNLOAD_FAILED = "Download failed" self.NO_BACKEND_SELECTED = "No backend selected" self.NO_MODEL_SELECTED = "No model selected" self.REFRESH_RELEASES = "Refresh Releases" self.NO_SUITABLE_CUDA_BACKENDS = "No suitable CUDA backends found" self.LLAMACPP_DOWNLOADED_EXTRACTED = "llama.cpp binary downloaded and extracted to {0}\nCUDA files extracted to {1}" self.CUDA_FILES_EXTRACTED = "CUDA files extracted to" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "No suitable CUDA backend found for extraction" ) self.ERROR_FETCHING_RELEASES = "Error fetching releases: {0}" self.CONFIRM_DELETION_TITLE = "Confirm Deletion" self.LOG_FOR = "Log for {0}" self.ALL_FILES = "All Files (*)" self.GGUF_FILES = "GGUF Files (*.gguf)" self.DAT_FILES = "DAT Files (*.dat)" self.JSON_FILES = "JSON Files (*.json)" self.FAILED_LOAD_PRESET = "Failed to load preset: {0}" self.INITIALIZING_AUTOGGUF = ( "Initialising AutoGGUF application" # Note the British spelling ) self.AUTOGGUF_INITIALIZATION_COMPLETE = ( "AutoGGUF initialisation complete" # Note the British spelling ) self.REFRESHING_BACKENDS = "Refreshing backends" self.NO_BACKENDS_AVAILABLE = "No backends available" self.FOUND_VALID_BACKENDS = "Found {0} valid backends" self.SAVING_PRESET = "Saving preset" self.PRESET_SAVED_TO = "Preset saved to {0}" self.LOADING_PRESET = "Loading preset" self.PRESET_LOADED_FROM = "Preset loaded from {0}" self.ADDING_KV_OVERRIDE = "Adding KV override: {0}" self.SAVING_TASK_PRESET = "Saving task preset for {0}" self.TASK_PRESET_SAVED = "Task Preset Saved" self.TASK_PRESET_SAVED_TO = "Task preset saved to {0}" self.RESTARTING_TASK = "Restarting task: {0}" self.IN_PROGRESS = "In Progress" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "Download finished. Extracted to: {0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "llama.cpp binary downloaded and extracted to {0}\nCUDA files extracted to {1}" self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "No suitable CUDA backend found for extraction" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "llama.cpp binary downloaded and extracted to {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "Refreshing llama.cpp releases" self.UPDATING_ASSET_LIST = "Updating asset list" self.UPDATING_CUDA_OPTIONS = "Updating CUDA options" self.STARTING_LLAMACPP_DOWNLOAD = "Starting llama.cpp download" self.UPDATING_CUDA_BACKENDS = "Updating CUDA backends" self.NO_CUDA_BACKEND_SELECTED = "No CUDA backend selected for extraction" self.EXTRACTING_CUDA_FILES = "Extracting CUDA files from {0} to {1}" self.DOWNLOAD_ERROR = "Download error: {0}" self.SHOWING_TASK_CONTEXT_MENU = "Showing task context menu" self.SHOWING_PROPERTIES_FOR_TASK = "Showing properties for task: {0}" self.CANCELLING_TASK = "Cancelling task: {0}" self.CANCELED = "Cancelled" self.DELETING_TASK = "Deleting task: {0}" self.LOADING_MODELS = "Loading models" self.LOADED_MODELS = "Loaded {0} models" self.BROWSING_FOR_MODELS_DIRECTORY = "Browsing for models directory" self.SELECT_MODELS_DIRECTORY = "Select Models Directory" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Browsing for output directory" self.SELECT_OUTPUT_DIRECTORY = "Select Output Directory" self.BROWSING_FOR_LOGS_DIRECTORY = "Browsing for logs directory" self.SELECT_LOGS_DIRECTORY = "Select Logs Directory" self.BROWSING_FOR_IMATRIX_FILE = "Browsing for IMatrix file" self.SELECT_IMATRIX_FILE = "Select IMatrix File" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "CPU Usage: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = ( "Validating quantisation inputs" # Note the British spelling ) self.MODELS_PATH_REQUIRED = "Models path is required" self.OUTPUT_PATH_REQUIRED = "Output path is required" self.LOGS_PATH_REQUIRED = "Logs path is required" self.STARTING_MODEL_QUANTIZATION = ( "Starting model quantisation" # Note the British spelling ) self.INPUT_FILE_NOT_EXIST = "Input file '{0}' does not exist." self.QUANTIZING_MODEL_TO = "Quantizing {0} to {1}" self.QUANTIZATION_TASK_STARTED = ( "Quantisation task started for {0}" # Note the British spelling ) self.ERROR_STARTING_QUANTIZATION = ( "Error starting quantisation: {0}" # Note the British spelling ) self.UPDATING_MODEL_INFO = "Updating model info: {0}" self.TASK_FINISHED = "Task finished: {0}" self.SHOWING_TASK_DETAILS_FOR = "Showing task details for: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "Browsing for IMatrix data file" self.SELECT_DATA_FILE = "Select Data File" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "Browsing for IMatrix model file" self.SELECT_MODEL_FILE = "Select Model File" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "Browsing for IMatrix output file" self.SELECT_OUTPUT_FILE = "Select Output File" self.STARTING_IMATRIX_GENERATION = "Starting IMatrix generation" self.BACKEND_PATH_NOT_EXIST = "Backend path does not exist: {0}" self.GENERATING_IMATRIX = "Generating IMatrix" self.ERROR_STARTING_IMATRIX_GENERATION = ( "Error starting IMatrix generation: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "IMatrix generation task started" self.ERROR_MESSAGE = "Error: {0}" self.TASK_ERROR = "Task error: {0}" self.APPLICATION_CLOSING = "Application closing" self.APPLICATION_CLOSED = "Application closed" self.SELECT_QUANTIZATION_TYPE = ( "Select the quantisation type" # Note the British spelling ) self.ALLOWS_REQUANTIZING = "Allows requantising tensors that have already been quantised" # Note the British spelling self.LEAVE_OUTPUT_WEIGHT = "Will leave output.weight un(re)quantised" self.DISABLE_K_QUANT_MIXTURES = "Disable k-quant mixtures and quantise all tensors to the same type" # Note the British spelling self.USE_DATA_AS_IMPORTANCE_MATRIX = "Use data in file as importance matrix for quant optimisations" # Note the British spelling self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Use importance matrix for these tensors" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Don't use importance matrix for these tensors" ) self.OUTPUT_TENSOR_TYPE = "Output Tensor Type:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Use this type for the output.weight tensor" ) self.TOKEN_EMBEDDING_TYPE = "Token Embedding Type:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Use this type for the token embeddings tensor" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = "Will generate quantised model in the same shards as input" # Note the British spelling self.OVERRIDE_MODEL_METADATA = "Override model metadata" self.INPUT_DATA_FILE_FOR_IMATRIX = "Input data file for IMatrix generation" self.MODEL_TO_BE_QUANTIZED = ( "Model to be quantised" # Note the British spelling ) self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = "Output path for the generated IMatrix" self.HOW_OFTEN_TO_SAVE_IMATRIX = "How often to save the IMatrix" self.SET_GPU_OFFLOAD_VALUE = "Set GPU offload value (-ngl)" self.COMPLETED = "Completed" self.REFRESH_MODELS = "Refresh Models" class _IndianEnglish(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (automated GGUF model quantizer)" self.RAM_USAGE = "RAM Usage:" self.CPU_USAGE = "CPU Usage:" self.BACKEND = "Llama.cpp Backend:" self.REFRESH_BACKENDS = "Refresh Backends" self.MODELS_PATH = "Models Path:" self.OUTPUT_PATH = "Output Path:" self.LOGS_PATH = "Logs Path:" self.BROWSE = "Browse" self.AVAILABLE_MODELS = "Available Models:" self.QUANTIZATION_TYPE = "Quantization Type:" self.ALLOW_REQUANTIZE = "Allow Requantize" self.LEAVE_OUTPUT_TENSOR = "Leave Output Tensor" self.PURE = "Pure" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "Include Weights:" self.EXCLUDE_WEIGHTS = "Exclude Weights:" self.USE_OUTPUT_TENSOR_TYPE = "Use Output Tensor Type" self.USE_TOKEN_EMBEDDING_TYPE = "Use Token Embedding Type" self.KEEP_SPLIT = "Keep Split" self.KV_OVERRIDES = "KV Overrides:" self.ADD_NEW_OVERRIDE = "Add new override" self.QUANTIZE_MODEL = "Quantize Model" self.SAVE_PRESET = "Save Preset" self.LOAD_PRESET = "Load Preset" self.TASKS = "Tasks:" self.DOWNLOAD_LLAMACPP = "Download llama.cpp" self.SELECT_RELEASE = "Select Release:" self.SELECT_ASSET = "Select Asset:" self.EXTRACT_CUDA_FILES = "Extract CUDA files" self.SELECT_CUDA_BACKEND = "Select CUDA Backend:" self.DOWNLOAD = "Download" self.IMATRIX_GENERATION = "IMatrix Generation" self.DATA_FILE = "Data File:" self.MODEL = "Model:" self.OUTPUT = "Output:" self.OUTPUT_FREQUENCY = "Output Frequency:" self.GPU_OFFLOAD = "GPU Offload:" self.AUTO = "Auto" self.GENERATE_IMATRIX = "Generate IMatrix" self.ERROR = "Error" self.WARNING = "Warning" self.PROPERTIES = "Properties" self.CANCEL = "Cancel" self.RESTART = "Restart" self.DELETE = "Delete" self.CONFIRM_DELETION = "Are you sure you want to delete this task?" self.TASK_RUNNING_WARNING = ( "Some tasks are still running. Are you sure you want to quit?" ) self.YES = "Yes" self.NO = "No" self.DOWNLOAD_COMPLETE = "Download Complete" self.CUDA_EXTRACTION_FAILED = "CUDA Extraction Failed" self.PRESET_SAVED = "Preset Saved" self.PRESET_LOADED = "Preset Loaded" self.NO_ASSET_SELECTED = "No asset selected" self.DOWNLOAD_FAILED = "Download failed" self.NO_BACKEND_SELECTED = "No backend selected" self.NO_MODEL_SELECTED = "No model selected" self.REFRESH_RELEASES = "Refresh Releases" self.NO_SUITABLE_CUDA_BACKENDS = "No suitable CUDA backends found" self.LLAMACPP_DOWNLOADED_EXTRACTED = "llama.cpp binary downloaded and extracted to {0}\nCUDA files extracted to {1}" self.CUDA_FILES_EXTRACTED = "CUDA files extracted to" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "No suitable CUDA backend found for extraction" ) self.ERROR_FETCHING_RELEASES = "Error fetching releases: {0}" self.CONFIRM_DELETION_TITLE = "Confirm Deletion" self.LOG_FOR = "Log for {0}" self.ALL_FILES = "All Files (*)" self.GGUF_FILES = "GGUF Files (*.gguf)" self.DAT_FILES = "DAT Files (*.dat)" self.JSON_FILES = "JSON Files (*.json)" self.FAILED_LOAD_PRESET = "Failed to load preset: {0}" self.INITIALIZING_AUTOGGUF = "Initializing AutoGGUF application" self.AUTOGGUF_INITIALIZATION_COMPLETE = "AutoGGUF initialization complete" self.REFRESHING_BACKENDS = "Refreshing backends" self.NO_BACKENDS_AVAILABLE = "No backends available" self.FOUND_VALID_BACKENDS = "Found {0} valid backends" self.SAVING_PRESET = "Saving preset" self.PRESET_SAVED_TO = "Preset saved to {0}" self.LOADING_PRESET = "Loading preset" self.PRESET_LOADED_FROM = "Preset loaded from {0}" self.ADDING_KV_OVERRIDE = "Adding KV override: {0}" self.SAVING_TASK_PRESET = "Saving task preset for {0}" self.TASK_PRESET_SAVED = "Task Preset Saved" self.TASK_PRESET_SAVED_TO = "Task preset saved to {0}" self.RESTARTING_TASK = "Restarting task: {0}" self.IN_PROGRESS = "In Progress" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "Download finished. Extracted to: {0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "llama.cpp binary downloaded and extracted to {0}\nCUDA files extracted to {1}" self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "No suitable CUDA backend found for extraction" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "llama.cpp binary downloaded and extracted to {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "Refreshing llama.cpp releases" self.UPDATING_ASSET_LIST = "Updating asset list" self.UPDATING_CUDA_OPTIONS = "Updating CUDA options" self.STARTING_LLAMACPP_DOWNLOAD = "Starting llama.cpp download" self.UPDATING_CUDA_BACKENDS = "Updating CUDA backends" self.NO_CUDA_BACKEND_SELECTED = "No CUDA backend selected for extraction" self.EXTRACTING_CUDA_FILES = "Extracting CUDA files from {0} to {1}" self.DOWNLOAD_ERROR = "Download error: {0}" self.SHOWING_TASK_CONTEXT_MENU = "Showing task context menu" self.SHOWING_PROPERTIES_FOR_TASK = "Showing properties for task: {0}" self.CANCELLING_TASK = "Cancelling task: {0}" self.CANCELED = "Cancelled" self.DELETING_TASK = "Deleting task: {0}" self.LOADING_MODELS = "Loading models" self.LOADED_MODELS = "Loaded {0} models" self.BROWSING_FOR_MODELS_DIRECTORY = "Browsing for models directory" self.SELECT_MODELS_DIRECTORY = "Select Models Directory" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Browsing for output directory" self.SELECT_OUTPUT_DIRECTORY = "Select Output Directory" self.BROWSING_FOR_LOGS_DIRECTORY = "Browsing for logs directory" self.SELECT_LOGS_DIRECTORY = "Select Logs Directory" self.BROWSING_FOR_IMATRIX_FILE = "Browsing for IMatrix file" self.SELECT_IMATRIX_FILE = "Select IMatrix File" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "CPU Usage: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "Validating quantization inputs" self.MODELS_PATH_REQUIRED = "Models path is required" self.OUTPUT_PATH_REQUIRED = "Output path is required" self.LOGS_PATH_REQUIRED = "Logs path is required" self.STARTING_MODEL_QUANTIZATION = "Starting model quantization" self.INPUT_FILE_NOT_EXIST = "Input file '{0}' does not exist." self.QUANTIZING_MODEL_TO = "Quantizing {0} to {1}" self.QUANTIZATION_TASK_STARTED = "Quantization task started for {0}" self.ERROR_STARTING_QUANTIZATION = "Error starting quantization: {0}" self.UPDATING_MODEL_INFO = "Updating model info: {0}" self.TASK_FINISHED = "Task finished: {0}" self.SHOWING_TASK_DETAILS_FOR = "Showing task details for: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "Browsing for IMatrix data file" self.SELECT_DATA_FILE = "Select Data File" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "Browsing for IMatrix model file" self.SELECT_MODEL_FILE = "Select Model File" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "Browsing for IMatrix output file" self.SELECT_OUTPUT_FILE = "Select Output File" self.STARTING_IMATRIX_GENERATION = "Starting IMatrix generation" self.BACKEND_PATH_NOT_EXIST = "Backend path does not exist: {0}" self.GENERATING_IMATRIX = "Generating IMatrix" self.ERROR_STARTING_IMATRIX_GENERATION = ( "Error starting IMatrix generation: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "IMatrix generation task started" self.ERROR_MESSAGE = "Error: {0}" self.TASK_ERROR = "Task error: {0}" self.APPLICATION_CLOSING = "Application closing" self.APPLICATION_CLOSED = "Application closed" self.SELECT_QUANTIZATION_TYPE = "Select the quantization type" self.ALLOWS_REQUANTIZING = ( "Allows requantizing tensors that have already been quantized" ) self.LEAVE_OUTPUT_WEIGHT = "Will leave output.weight un(re)quantized" self.DISABLE_K_QUANT_MIXTURES = ( "Disable k-quant mixtures and quantize all tensors to the same type" ) self.USE_DATA_AS_IMPORTANCE_MATRIX = ( "Use data in file as importance matrix for quant optimisations" ) self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Use importance matrix for these tensors" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Don't use importance matrix for these tensors" ) self.OUTPUT_TENSOR_TYPE = "Output Tensor Type:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Use this type for the output.weight tensor" ) self.TOKEN_EMBEDDING_TYPE = "Token Embedding Type:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Use this type for the token embeddings tensor" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "Will generate quantized model in the same shards as input" ) self.OVERRIDE_MODEL_METADATA = "Override model metadata" self.INPUT_DATA_FILE_FOR_IMATRIX = "Input data file for IMatrix generation" self.MODEL_TO_BE_QUANTIZED = "Model to be quantized" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = "Output path for the generated IMatrix" self.HOW_OFTEN_TO_SAVE_IMATRIX = "How often to save the IMatrix" self.SET_GPU_OFFLOAD_VALUE = "Set GPU offload value (-ngl)" self.COMPLETED = "Completed" self.REFRESH_MODELS = "Refresh Models" class _CanadianEnglish(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF (automated GGUF model quantizer)" self.RAM_USAGE = "RAM Usage:" self.CPU_USAGE = "CPU Usage:" self.BACKEND = "Llama.cpp Backend:" self.REFRESH_BACKENDS = "Refresh Backends" self.MODELS_PATH = "Models Path:" self.OUTPUT_PATH = "Output Path:" self.LOGS_PATH = "Logs Path:" self.BROWSE = "Browse" self.AVAILABLE_MODELS = "Available Models:" self.QUANTIZATION_TYPE = "Quantization Type:" self.ALLOW_REQUANTIZE = "Allow Requantize" self.LEAVE_OUTPUT_TENSOR = "Leave Output Tensor" self.PURE = "Pure" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "Include Weights:" self.EXCLUDE_WEIGHTS = "Exclude Weights:" self.USE_OUTPUT_TENSOR_TYPE = "Use Output Tensor Type" self.USE_TOKEN_EMBEDDING_TYPE = "Use Token Embedding Type" self.KEEP_SPLIT = "Keep Split" self.KV_OVERRIDES = "KV Overrides:" self.ADD_NEW_OVERRIDE = "Add new override" self.QUANTIZE_MODEL = "Quantize Model" self.SAVE_PRESET = "Save Preset" self.LOAD_PRESET = "Load Preset" self.TASKS = "Tasks:" self.DOWNLOAD_LLAMACPP = "Download llama.cpp" self.SELECT_RELEASE = "Select Release:" self.SELECT_ASSET = "Select Asset:" self.EXTRACT_CUDA_FILES = "Extract CUDA files" self.SELECT_CUDA_BACKEND = "Select CUDA Backend:" self.DOWNLOAD = "Download" self.IMATRIX_GENERATION = "IMatrix Generation" self.DATA_FILE = "Data File:" self.MODEL = "Model:" self.OUTPUT = "Output:" self.OUTPUT_FREQUENCY = "Output Frequency:" self.GPU_OFFLOAD = "GPU Offload:" self.AUTO = "Auto" self.GENERATE_IMATRIX = "Generate IMatrix" self.ERROR = "Error" self.WARNING = "Warning" self.PROPERTIES = "Properties" self.CANCEL = "Cancel" self.RESTART = "Restart" self.DELETE = "Delete" self.CONFIRM_DELETION = "Are you sure you want to delete this task?" self.TASK_RUNNING_WARNING = ( "Some tasks are still running. Are you sure you want to quit?" ) self.YES = "Yes" self.NO = "No" self.DOWNLOAD_COMPLETE = "Download Complete" self.CUDA_EXTRACTION_FAILED = "CUDA Extraction Failed" self.PRESET_SAVED = "Preset Saved" self.PRESET_LOADED = "Preset Loaded" self.NO_ASSET_SELECTED = "No asset selected" self.DOWNLOAD_FAILED = "Download failed" self.NO_BACKEND_SELECTED = "No backend selected" self.NO_MODEL_SELECTED = "No model selected" self.REFRESH_RELEASES = "Refresh Releases" self.NO_SUITABLE_CUDA_BACKENDS = "No suitable CUDA backends found" self.LLAMACPP_DOWNLOADED_EXTRACTED = "llama.cpp binary downloaded and extracted to {0}\nCUDA files extracted to {1}" self.CUDA_FILES_EXTRACTED = "CUDA files extracted to" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = ( "No suitable CUDA backend found for extraction" ) self.ERROR_FETCHING_RELEASES = "Error fetching releases: {0}" self.CONFIRM_DELETION_TITLE = "Confirm Deletion" self.LOG_FOR = "Log for {0}" self.ALL_FILES = "All Files (*)" self.GGUF_FILES = "GGUF Files (*.gguf)" self.DAT_FILES = "DAT Files (*.dat)" self.JSON_FILES = "JSON Files (*.json)" self.FAILED_LOAD_PRESET = "Failed to load preset: {0}" self.INITIALIZING_AUTOGGUF = "Initializing AutoGGUF application" self.AUTOGGUF_INITIALIZATION_COMPLETE = "AutoGGUF initialization complete" self.REFRESHING_BACKENDS = "Refreshing backends" self.NO_BACKENDS_AVAILABLE = "No backends available" self.FOUND_VALID_BACKENDS = "Found {0} valid backends" self.SAVING_PRESET = "Saving preset" self.PRESET_SAVED_TO = "Preset saved to {0}" self.LOADING_PRESET = "Loading preset" self.PRESET_LOADED_FROM = "Preset loaded from {0}" self.ADDING_KV_OVERRIDE = "Adding KV override: {0}" self.SAVING_TASK_PRESET = "Saving task preset for {0}" self.TASK_PRESET_SAVED = "Task Preset Saved" self.TASK_PRESET_SAVED_TO = "Task preset saved to {0}" self.RESTARTING_TASK = "Restarting task: {0}" self.IN_PROGRESS = "In Progress" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "Download finished. Extracted to: {0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = "llama.cpp binary downloaded and extracted to {0}\nCUDA files extracted to {1}" self.NO_SUITABLE_CUDA_BACKEND_FOUND = ( "No suitable CUDA backend found for extraction" ) self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "llama.cpp binary downloaded and extracted to {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "Refreshing llama.cpp releases" self.UPDATING_ASSET_LIST = "Updating asset list" self.UPDATING_CUDA_OPTIONS = "Updating CUDA options" self.STARTING_LLAMACPP_DOWNLOAD = "Starting llama.cpp download" self.UPDATING_CUDA_BACKENDS = "Updating CUDA backends" self.NO_CUDA_BACKEND_SELECTED = "No CUDA backend selected for extraction" self.EXTRACTING_CUDA_FILES = "Extracting CUDA files from {0} to {1}" self.DOWNLOAD_ERROR = "Download error: {0}" self.SHOWING_TASK_CONTEXT_MENU = "Showing task context menu" self.SHOWING_PROPERTIES_FOR_TASK = "Showing properties for task: {0}" self.CANCELLING_TASK = "Cancelling task: {0}" self.CANCELED = "Cancelled" self.DELETING_TASK = "Deleting task: {0}" self.LOADING_MODELS = "Loading models" self.LOADED_MODELS = "Loaded {0} models" self.BROWSING_FOR_MODELS_DIRECTORY = "Browsing for models directory" self.SELECT_MODELS_DIRECTORY = "Select Models Directory" self.BROWSING_FOR_OUTPUT_DIRECTORY = "Browsing for output directory" self.SELECT_OUTPUT_DIRECTORY = "Select Output Directory" self.BROWSING_FOR_LOGS_DIRECTORY = "Browsing for logs directory" self.SELECT_LOGS_DIRECTORY = "Select Logs Directory" self.BROWSING_FOR_IMATRIX_FILE = "Browsing for IMatrix file" self.SELECT_IMATRIX_FILE = "Select IMatrix File" self.RAM_USAGE_FORMAT = "{0:.1f}% ({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "CPU Usage: {0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "Validating quantization inputs" self.MODELS_PATH_REQUIRED = "Models path is required" self.OUTPUT_PATH_REQUIRED = "Output path is required" self.LOGS_PATH_REQUIRED = "Logs path is required" self.STARTING_MODEL_QUANTIZATION = "Starting model quantization" self.INPUT_FILE_NOT_EXIST = "Input file '{0}' does not exist." self.QUANTIZING_MODEL_TO = "Quantizing {0} to {1}" self.QUANTIZATION_TASK_STARTED = "Quantization task started for {0}" self.ERROR_STARTING_QUANTIZATION = "Error starting quantization: {0}" self.UPDATING_MODEL_INFO = "Updating model info: {0}" self.TASK_FINISHED = "Task finished: {0}" self.SHOWING_TASK_DETAILS_FOR = "Showing task details for: {0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "Browsing for IMatrix data file" self.SELECT_DATA_FILE = "Select Data File" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "Browsing for IMatrix model file" self.SELECT_MODEL_FILE = "Select Model File" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "Browsing for IMatrix output file" self.SELECT_OUTPUT_FILE = "Select Output File" self.STARTING_IMATRIX_GENERATION = "Starting IMatrix generation" self.BACKEND_PATH_NOT_EXIST = "Backend path does not exist: {0}" self.GENERATING_IMATRIX = "Generating IMatrix" self.ERROR_STARTING_IMATRIX_GENERATION = ( "Error starting IMatrix generation: {0}" ) self.IMATRIX_GENERATION_TASK_STARTED = "IMatrix generation task started" self.ERROR_MESSAGE = "Error: {0}" self.TASK_ERROR = "Task error: {0}" self.APPLICATION_CLOSING = "Application closing" self.APPLICATION_CLOSED = "Application closed" self.SELECT_QUANTIZATION_TYPE = "Select the quantization type" self.ALLOWS_REQUANTIZING = ( "Allows requantizing tensors that have already been quantized" ) self.LEAVE_OUTPUT_WEIGHT = "Will leave output.weight un(re)quantized" self.DISABLE_K_QUANT_MIXTURES = ( "Disable k-quant mixtures and quantize all tensors to the same type" ) self.USE_DATA_AS_IMPORTANCE_MATRIX = ( "Use data in file as importance matrix for quant optimisations" ) self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Use importance matrix for these tensors" ) self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = ( "Don't use importance matrix for these tensors" ) self.OUTPUT_TENSOR_TYPE = "Output Tensor Type:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = ( "Use this type for the output.weight tensor" ) self.TOKEN_EMBEDDING_TYPE = "Token Embedding Type:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = ( "Use this type for the token embeddings tensor" ) self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "Will generate quantized model in the same shards as input" ) self.OVERRIDE_MODEL_METADATA = "Override model metadata" self.INPUT_DATA_FILE_FOR_IMATRIX = "Input data file for IMatrix generation" self.MODEL_TO_BE_QUANTIZED = "Model to be quantized" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = "Output path for the generated IMatrix" self.HOW_OFTEN_TO_SAVE_IMATRIX = "How often to save the IMatrix" self.SET_GPU_OFFLOAD_VALUE = "Set GPU offload value (-ngl)" self.COMPLETED = "Completed" self.REFRESH_MODELS = "Refresh Models" class _TraditionalChinese(_Localization): def __init__(self): super().__init__() self.WINDOW_TITLE = "AutoGGUF(自動 GGUF 模型量化器)" self.RAM_USAGE = "RAM 使用量:" self.CPU_USAGE = "CPU 使用率:" self.BACKEND = "Llama.cpp 後端:" self.REFRESH_BACKENDS = "重新整理後端" self.MODELS_PATH = "模型路徑:" self.OUTPUT_PATH = "輸出路徑:" self.LOGS_PATH = "日誌路徑:" self.BROWSE = "瀏覽" self.AVAILABLE_MODELS = "可用模型:" self.QUANTIZATION_TYPE = "量化類型:" self.ALLOW_REQUANTIZE = "允許重新量化" self.LEAVE_OUTPUT_TENSOR = "保留輸出張量" self.PURE = "純粹" self.IMATRIX = "IMatrix:" self.INCLUDE_WEIGHTS = "包含權重:" self.EXCLUDE_WEIGHTS = "排除權重:" self.USE_OUTPUT_TENSOR_TYPE = "使用輸出張量類型" self.USE_TOKEN_EMBEDDING_TYPE = "使用權杖嵌入類型" self.KEEP_SPLIT = "保持分割" self.KV_OVERRIDES = "KV 覆蓋:" self.ADD_NEW_OVERRIDE = "新增覆蓋" self.QUANTIZE_MODEL = "量化模型" self.SAVE_PRESET = "儲存預設" self.LOAD_PRESET = "載入預設" self.TASKS = "任務:" self.DOWNLOAD_LLAMACPP = "下載 llama.cpp" self.SELECT_RELEASE = "選擇版本:" self.SELECT_ASSET = "選擇資源:" self.EXTRACT_CUDA_FILES = "解壓縮 CUDA 檔案" self.SELECT_CUDA_BACKEND = "選擇 CUDA 後端:" self.DOWNLOAD = "下載" self.IMATRIX_GENERATION = "IMatrix 產生" self.DATA_FILE = "資料檔案:" self.MODEL = "模型:" self.OUTPUT = "輸出:" self.OUTPUT_FREQUENCY = "輸出頻率:" self.GPU_OFFLOAD = "GPU 卸載:" self.AUTO = "自動" self.GENERATE_IMATRIX = "產生 IMatrix" self.ERROR = "錯誤" self.WARNING = "警告" self.PROPERTIES = "屬性" self.CANCEL = "取消" self.RESTART = "重新啟動" self.DELETE = "刪除" self.CONFIRM_DELETION = "您確定要刪除此任務嗎?" self.TASK_RUNNING_WARNING = "某些任務仍在執行中。您確定要結束嗎?" self.YES = "是" self.NO = "否" self.DOWNLOAD_COMPLETE = "下載完成" self.CUDA_EXTRACTION_FAILED = "CUDA 解壓縮失敗" self.PRESET_SAVED = "預設已儲存" self.PRESET_LOADED = "預設已載入" self.NO_ASSET_SELECTED = "未選擇資源" self.DOWNLOAD_FAILED = "下載失敗" self.NO_BACKEND_SELECTED = "未選擇後端" self.NO_MODEL_SELECTED = "未選擇模型" self.REFRESH_RELEASES = "重新整理版本" self.NO_SUITABLE_CUDA_BACKENDS = "找不到合適的 CUDA 後端" self.LLAMACPP_DOWNLOADED_EXTRACTED = ( "llama.cpp 二進位檔案已下載並解壓縮至 {0}\nCUDA 檔案已解壓縮至 {1}" ) self.CUDA_FILES_EXTRACTED = "CUDA 檔案已解壓縮至" self.NO_SUITABLE_CUDA_BACKEND_EXTRACTION = "找不到合適的 CUDA 後端進行解壓縮" self.ERROR_FETCHING_RELEASES = "擷取版本時發生錯誤:{0}" self.CONFIRM_DELETION_TITLE = "確認刪除" self.LOG_FOR = "{0} 的日誌" self.ALL_FILES = "所有檔案 (*)" self.GGUF_FILES = "GGUF 檔案 (*.gguf)" self.DAT_FILES = "DAT 檔案 (*.dat)" self.JSON_FILES = "JSON 檔案 (*.json)" self.FAILED_LOAD_PRESET = "載入預設失敗:{0}" self.INITIALIZING_AUTOGGUF = "正在初始化 AutoGGUF 應用程式" self.AUTOGGUF_INITIALIZATION_COMPLETE = "AutoGGUF 初始化完成" self.REFRESHING_BACKENDS = "正在重新整理後端" self.NO_BACKENDS_AVAILABLE = "沒有可用的後端" self.FOUND_VALID_BACKENDS = "找到 {0} 個有效的後端" self.SAVING_PRESET = "正在儲存預設" self.PRESET_SAVED_TO = "預設已儲存至 {0}" self.LOADING_PRESET = "正在載入預設" self.PRESET_LOADED_FROM = "從 {0} 載入了預設" self.ADDING_KV_OVERRIDE = "正在新增 KV 覆蓋:{0}" self.SAVING_TASK_PRESET = "正在儲存 {0} 的任務預設" self.TASK_PRESET_SAVED = "任務預設已儲存" self.TASK_PRESET_SAVED_TO = "任務預設已儲存至 {0}" self.RESTARTING_TASK = "正在重新啟動任務:{0}" self.IN_PROGRESS = "處理中" self.DOWNLOAD_FINISHED_EXTRACTED_TO = "下載完成。已解壓縮至:{0}" self.LLAMACPP_DOWNLOADED_AND_EXTRACTED = ( "llama.cpp 二進位檔案已下載並解壓縮至 {0}\nCUDA 檔案已解壓縮至 {1}" ) self.NO_SUITABLE_CUDA_BACKEND_FOUND = "找不到合適的 CUDA 後端進行解壓縮" self.LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED = ( "llama.cpp 二進位檔案已下載並解壓縮至 {0}" ) self.REFRESHING_LLAMACPP_RELEASES = "正在重新整理 llama.cpp 版本" self.UPDATING_ASSET_LIST = "正在更新資源清單" self.UPDATING_CUDA_OPTIONS = "正在更新 CUDA 選項" self.STARTING_LLAMACPP_DOWNLOAD = "正在開始下載 llama.cpp" self.UPDATING_CUDA_BACKENDS = "正在更新 CUDA 後端" self.NO_CUDA_BACKEND_SELECTED = "未選擇要解壓縮的 CUDA 後端" self.EXTRACTING_CUDA_FILES = "正在從 {0} 解壓縮 CUDA 檔案至 {1}" self.DOWNLOAD_ERROR = "下載錯誤:{0}" self.SHOWING_TASK_CONTEXT_MENU = "正在顯示任務操作選單" self.SHOWING_PROPERTIES_FOR_TASK = "正在顯示任務的屬性:{0}" self.CANCELLING_TASK = "正在取消任務:{0}" self.CANCELED = "已取消" self.DELETING_TASK = "正在刪除任務:{0}" self.LOADING_MODELS = "正在載入模型" self.LOADED_MODELS = "已載入 {0} 個模型" self.BROWSING_FOR_MODELS_DIRECTORY = "正在瀏覽模型目錄" self.SELECT_MODELS_DIRECTORY = "選擇模型目錄" self.BROWSING_FOR_OUTPUT_DIRECTORY = "正在瀏覽輸出目錄" self.SELECT_OUTPUT_DIRECTORY = "選擇輸出目錄" self.BROWSING_FOR_LOGS_DIRECTORY = "正在瀏覽日誌目錄" self.SELECT_LOGS_DIRECTORY = "選擇日誌目錄" self.BROWSING_FOR_IMATRIX_FILE = "正在瀏覽 IMatrix 檔案" self.SELECT_IMATRIX_FILE = "選擇 IMatrix 檔案" self.RAM_USAGE_FORMAT = "{0:.1f}%({1} MB / {2} MB)" self.CPU_USAGE_FORMAT = "CPU 使用率:{0:.1f}%" self.VALIDATING_QUANTIZATION_INPUTS = "正在驗證量化輸入" self.MODELS_PATH_REQUIRED = "需要模型路徑" self.OUTPUT_PATH_REQUIRED = "需要輸出路徑" self.LOGS_PATH_REQUIRED = "需要日誌路徑" self.STARTING_MODEL_QUANTIZATION = "正在開始模型量化" self.INPUT_FILE_NOT_EXIST = "輸入檔案 '{0}' 不存在。" self.QUANTIZING_MODEL_TO = "正在將 {0} 量化為 {1}" self.QUANTIZATION_TASK_STARTED = "已啟動 {0} 的量化任務" self.ERROR_STARTING_QUANTIZATION = "啟動量化時發生錯誤:{0}" self.UPDATING_MODEL_INFO = "正在更新模型資訊:{0}" self.TASK_FINISHED = "任務完成:{0}" self.SHOWING_TASK_DETAILS_FOR = "正在顯示任務詳細資訊:{0}" self.BROWSING_FOR_IMATRIX_DATA_FILE = "正在瀏覽 IMatrix 資料檔案" self.SELECT_DATA_FILE = "選擇資料檔案" self.BROWSING_FOR_IMATRIX_MODEL_FILE = "正在瀏覽 IMatrix 模型檔案" self.SELECT_MODEL_FILE = "選擇模型檔案" self.BROWSING_FOR_IMATRIX_OUTPUT_FILE = "正在瀏覽 IMatrix 輸出檔案" self.SELECT_OUTPUT_FILE = "選擇輸出檔案" self.STARTING_IMATRIX_GENERATION = "正在開始 IMatrix 產生" self.BACKEND_PATH_NOT_EXIST = "後端路徑不存在:{0}" self.GENERATING_IMATRIX = "正在產生 IMatrix" self.ERROR_STARTING_IMATRIX_GENERATION = "啟動 IMatrix 產生時發生錯誤:{0}" self.IMATRIX_GENERATION_TASK_STARTED = "IMatrix 產生任務已啟動" self.ERROR_MESSAGE = "錯誤:{0}" self.TASK_ERROR = "任務錯誤:{0}" self.APPLICATION_CLOSING = "應用程式正在關閉" self.APPLICATION_CLOSED = "應用程式已關閉" self.SELECT_QUANTIZATION_TYPE = "請選擇量化類型" self.ALLOWS_REQUANTIZING = "允許重新量化已量化的張量" self.LEAVE_OUTPUT_WEIGHT = "將保留 output.weight 不被(重新)量化" self.DISABLE_K_QUANT_MIXTURES = "停用 k-quant 混合並將所有張量量化為相同類型" self.USE_DATA_AS_IMPORTANCE_MATRIX = ( "使用檔案中的資料作為量化最佳化的重要性矩陣" ) self.USE_IMPORTANCE_MATRIX_FOR_TENSORS = "對這些張量使用重要性矩陣" self.DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS = "不要對這些張量使用重要性矩陣" self.OUTPUT_TENSOR_TYPE = "輸出張量類型:" self.USE_THIS_TYPE_FOR_OUTPUT_WEIGHT = "對 output.weight 張量使用此類型" self.TOKEN_EMBEDDING_TYPE = "權杖嵌入類型:" self.USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS = "對權杖嵌入張量使用此類型" self.WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS = ( "將在與輸入相同的分片中產生量化模型" ) self.OVERRIDE_MODEL_METADATA = "覆蓋模型中繼資料" self.INPUT_DATA_FILE_FOR_IMATRIX = "IMatrix 產生的輸入資料檔案" self.MODEL_TO_BE_QUANTIZED = "要量化的模型" self.OUTPUT_PATH_FOR_GENERATED_IMATRIX = "產生的 IMatrix 的輸出路徑" self.HOW_OFTEN_TO_SAVE_IMATRIX = "儲存 IMatrix 的頻率" self.SET_GPU_OFFLOAD_VALUE = "設定 GPU 卸載值(-ngl)" self.COMPLETED = "已完成" self.REFRESH_MODELS = "重新整理模型" # fmt: off # Dictionary to map language codes to classes _languages = { "en-US": _English, # American English "fr-FR": _French, # Metropolitan French "zh-CN": _SimplifiedChinese, # Simplified Chinese "es-ES": _Spanish, # Spanish (Spain) "hi-IN": _Hindi, # Hindi (India) "ru-RU": _Russian, # Russian (Russia) "uk-UA": _Ukrainian, # Ukrainian (Ukraine) "ja-JP": _Japanese, # Japanese (Japan) "de-DE": _German, # German (Germany) "pt-BR": _Portuguese, # Portuguese (Brazil) "ar-SA": _Arabic, # Arabic (Saudi Arabia) "ko-KR": _Korean, # Korean (Korea) "it-IT": _Italian, # Italian (Italy) "tr-TR": _Turkish, # Turkish (Turkey) "nl-NL": _Dutch, # Dutch (Netherlands) "fi-FI": _Finnish, # Finnish (Finland) "bn-BD": _Bengali, # Bengali (Bangladesh) "cs-CZ": _Czech, # Czech (Czech Republic) "pl-PL": _Polish, # Polish (Poland) "ro-RO": _Romanian, # Romanian (Romania) "el-GR": _Greek, # Greek (Greece) "pt-PT": _Portuguese_PT, # Portuguese (Portugal) "hu-HU": _Hungarian, # Hungarian (Hungary) "en-GB": _BritishEnglish, # British English "fr-CA": _CanadianFrench, # Canadian French "en-IN": _IndianEnglish, # Indian English "en-CA": _CanadianEnglish, # Canadian English "zh-TW": _TraditionalChinese, # Traditional Chinese (Taiwan) } # fmt: on def set_language(lang_code): # Globals global WINDOW_TITLE, RAM_USAGE, CPU_USAGE, BACKEND, REFRESH_BACKENDS, MODELS_PATH, OUTPUT_PATH, LOGS_PATH global BROWSE, AVAILABLE_MODELS, QUANTIZATION_TYPE, ALLOW_REQUANTIZE, LEAVE_OUTPUT_TENSOR, PURE, IMATRIX global INCLUDE_WEIGHTS, EXCLUDE_WEIGHTS, USE_OUTPUT_TENSOR_TYPE, USE_TOKEN_EMBEDDING_TYPE, KEEP_SPLIT global KV_OVERRIDES, ADD_NEW_OVERRIDE, QUANTIZE_MODEL, SAVE_PRESET, LOAD_PRESET, TASKS, DOWNLOAD_LLAMACPP global SELECT_RELEASE, SELECT_ASSET, EXTRACT_CUDA_FILES, SELECT_CUDA_BACKEND, DOWNLOAD, IMATRIX_GENERATION global DATA_FILE, MODEL, OUTPUT, OUTPUT_FREQUENCY, GPU_OFFLOAD, AUTO, GENERATE_IMATRIX, ERROR, WARNING global PROPERTIES, CANCEL, RESTART, DELETE, CONFIRM_DELETION, TASK_RUNNING_WARNING, YES, NO, DOWNLOAD_COMPLETE global CUDA_EXTRACTION_FAILED, PRESET_SAVED, PRESET_LOADED, NO_ASSET_SELECTED, DOWNLOAD_FAILED, NO_BACKEND_SELECTED global NO_MODEL_SELECTED, REFRESH_RELEASES, NO_SUITABLE_CUDA_BACKENDS, LLAMACPP_DOWNLOADED_EXTRACTED, CUDA_FILES_EXTRACTED global NO_SUITABLE_CUDA_BACKEND_EXTRACTION, ERROR_FETCHING_RELEASES, CONFIRM_DELETION_TITLE, LOG_FOR, ALL_FILES global GGUF_FILES, DAT_FILES, JSON_FILES, FAILED_LOAD_PRESET, INITIALIZING_AUTOGGUF, AUTOGGUF_INITIALIZATION_COMPLETE global REFRESHING_BACKENDS, NO_BACKENDS_AVAILABLE, FOUND_VALID_BACKENDS, SAVING_PRESET, PRESET_SAVED_TO, LOADING_PRESET global PRESET_LOADED_FROM, ADDING_KV_OVERRIDE, SAVING_TASK_PRESET, TASK_PRESET_SAVED, TASK_PRESET_SAVED_TO, RESTARTING_TASK global IN_PROGRESS, DOWNLOAD_FINISHED_EXTRACTED_TO, LLAMACPP_DOWNLOADED_AND_EXTRACTED, NO_SUITABLE_CUDA_BACKEND_FOUND global LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED, REFRESHING_LLAMACPP_RELEASES, UPDATING_ASSET_LIST, UPDATING_CUDA_OPTIONS global STARTING_LLAMACPP_DOWNLOAD, UPDATING_CUDA_BACKENDS, NO_CUDA_BACKEND_SELECTED, EXTRACTING_CUDA_FILES, DOWNLOAD_ERROR global SHOWING_TASK_CONTEXT_MENU, SHOWING_PROPERTIES_FOR_TASK, CANCELLING_TASK, CANCELED, DELETING_TASK, LOADING_MODELS, LOADED_MODELS global BROWSING_FOR_MODELS_DIRECTORY, SELECT_MODELS_DIRECTORY, BROWSING_FOR_OUTPUT_DIRECTORY, SELECT_OUTPUT_DIRECTORY global BROWSING_FOR_LOGS_DIRECTORY, SELECT_LOGS_DIRECTORY, BROWSING_FOR_IMATRIX_FILE, SELECT_IMATRIX_FILE, RAM_USAGE_FORMAT global CPU_USAGE_FORMAT, VALIDATING_QUANTIZATION_INPUTS, MODELS_PATH_REQUIRED, OUTPUT_PATH_REQUIRED, LOGS_PATH_REQUIRED global STARTING_MODEL_QUANTIZATION, INPUT_FILE_NOT_EXIST, QUANTIZING_MODEL_TO, QUANTIZATION_TASK_STARTED, ERROR_STARTING_QUANTIZATION global UPDATING_MODEL_INFO, TASK_FINISHED, SHOWING_TASK_DETAILS_FOR, BROWSING_FOR_IMATRIX_DATA_FILE, SELECT_DATA_FILE global BROWSING_FOR_IMATRIX_MODEL_FILE, SELECT_MODEL_FILE, BROWSING_FOR_IMATRIX_OUTPUT_FILE, SELECT_OUTPUT_FILE global STARTING_IMATRIX_GENERATION, BACKEND_PATH_NOT_EXIST, GENERATING_IMATRIX, ERROR_STARTING_IMATRIX_GENERATION global IMATRIX_GENERATION_TASK_STARTED, ERROR_MESSAGE, TASK_ERROR, APPLICATION_CLOSING, APPLICATION_CLOSED, SELECT_QUANTIZATION_TYPE global ALLOWS_REQUANTIZING, LEAVE_OUTPUT_WEIGHT, DISABLE_K_QUANT_MIXTURES, USE_DATA_AS_IMPORTANCE_MATRIX, USE_IMPORTANCE_MATRIX_FOR_TENSORS global DONT_USE_IMPORTANCE_MATRIX_FOR_TENSORS, OUTPUT_TENSOR_TYPE, USE_THIS_TYPE_FOR_OUTPUT_WEIGHT, TOKEN_EMBEDDING_TYPE, USE_THIS_TYPE_FOR_TOKEN_EMBEDDINGS global WILL_GENERATE_QUANTIZED_MODEL_IN_SAME_SHARDS, OVERRIDE_MODEL_METADATA, INPUT_DATA_FILE_FOR_IMATRIX, MODEL_TO_BE_QUANTIZED global OUTPUT_PATH_FOR_GENERATED_IMATRIX, HOW_OFTEN_TO_SAVE_IMATRIX, SET_GPU_OFFLOAD_VALUE, COMPLETED, REFRESH_MODELS global CONTEXT_SIZE, CONTEXT_SIZE_FOR_IMATRIX, THREADS, NUMBER_OF_THREADS_FOR_IMATRIX, EXTRA_ARGUMENTS, EXTRA_ARGUMENTS_LABEL global LORA_CONVERSION, LORA_INPUT_PATH, LORA_OUTPUT_PATH, SELECT_LORA_INPUT_DIRECTORY, SELECT_LORA_OUTPUT_FILE global CONVERT_LORA, STARTING_LORA_CONVERSION, LORA_INPUT_PATH_REQUIRED, LORA_OUTPUT_PATH_REQUIRED, ERROR_STARTING_LORA_CONVERSION global LORA_CONVERSION_TASK_STARTED, BIN_FILES, BROWSING_FOR_LORA_INPUT_DIRECTORY, BROWSING_FOR_LORA_OUTPUT_FILE, CONVERTING_LORA global LORA_CONVERSION_FINISHED, LORA_FILE_MOVED, LORA_FILE_NOT_FOUND, ERROR_MOVING_LORA_FILE, EXPORT_LORA global MODEL_PATH_REQUIRED, AT_LEAST_ONE_LORA_ADAPTER_REQUIRED, INVALID_LORA_SCALE_VALUE, ERROR_STARTING_LORA_EXPORT, LORA_EXPORT_TASK_STARTED global GGML_LORA_ADAPTERS, SELECT_LORA_ADAPTER_FILES, ADD_ADAPTER, DELETE_ADAPTER, LORA_SCALE global ENTER_LORA_SCALE_VALUE, NUMBER_OF_THREADS_FOR_LORA_EXPORT, EXPORTING_LORA, BROWSING_FOR_EXPORT_LORA_MODEL_FILE, BROWSING_FOR_EXPORT_LORA_OUTPUT_FILE global ADDING_LORA_ADAPTER, DELETING_LORA_ADAPTER, LORA_FILES, SELECT_LORA_ADAPTER_FILE, STARTING_LORA_EXPORT global OUTPUT_TYPE, SELECT_OUTPUT_TYPE, GGUF_AND_BIN_FILES, BASE_MODEL, SELECT_BASE_MODEL_FILE global BASE_MODEL_PATH_REQUIRED, BROWSING_FOR_BASE_MODEL_FILE, SELECT_BASE_MODEL_FOLDER, BROWSING_FOR_BASE_MODEL_FOLDER global LORA_CONVERSION_FROM_TO, GENERATING_IMATRIX_FOR, MODEL_PATH_REQUIRED_FOR_IMATRIX, NO_ASSET_SELECTED_FOR_CUDA_CHECK, QUANTIZATION_COMMAND global IMATRIX_GENERATION_COMMAND, LORA_CONVERSION_COMMAND, LORA_EXPORT_COMMAND global NO_QUANTIZATION_TYPE_SELECTED, STARTING_HF_TO_GGUF_CONVERSION, MODEL_DIRECTORY_REQUIRED global HF_TO_GGUF_CONVERSION_COMMAND, CONVERTING_TO_GGUF, ERROR_STARTING_HF_TO_GGUF_CONVERSION global HF_TO_GGUF_CONVERSION_TASK_STARTED, HF_TO_GGUF_CONVERSION, MODEL_DIRECTORY, OUTPUT_FILE global VOCAB_ONLY, USE_TEMP_FILE, NO_LAZY_EVALUATION, MODEL_NAME, VERBOSE, SPLIT_MAX_SIZE global DRY_RUN, CONVERT_HF_TO_GGUF, SELECT_HF_MODEL_DIRECTORY, BROWSE_FOR_HF_MODEL_DIRECTORY global BROWSE_FOR_HF_TO_GGUF_OUTPUT, SHARDED loc = _languages.get(lang_code, _English)() english_loc = _English() # Create an instance of English localization for fallback for key in dir(english_loc): if not key.startswith("_"): globals()[key] = getattr(loc, key, getattr(english_loc, key)) # Get the language from the AUTOGGUF_LANGUAGE environment variable, default to 'en' language_code = os.getenv("AUTOGGUF_LANGUAGE", "en-US") # Set default language set_language(language_code)