AutoGGUF - automated GGUF model quantizer

This application provides a graphical user interface for quantizing GGUF models using the llama.cpp library. It allows users to download different versions of llama.cpp, manage multiple backends, and perform quantization tasks with various options.

Main features:

1. Download and manage llama.cpp backends
2. Select and quantize GGUF models
3. Configure quantization parameters
4. Monitor system resources during quantization

Usage:

Cross platform:

1. Install dependencies, either using the requirements.txt file or pip install PyQt6 requests psutil.
2. Run the run.bat script to start the application, or run the command python src/main.py.

Windows:

1. Download latest release, extract all to folder and run AutoGGUF.exe
2. Enjoy!

Building:

Cross platform:

cd src
pip install -U pyinstaller
pyinstaller main.py --onefile
cd dist/main
./main

Windows:

build RELEASE/DEV

Find exe in build/<type>/dist/AutoGGUF.exe.

Dependencies:

• PyQt6
• requests
• psutil
• shutil
• OpenSSL

Localizations:

The following languages are currently supported (machine translated, except for English):

{
    '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)
}

In order to use them, please set the AUTOGGUF_LANGUAGE environment variable to one of the listed language codes.

Issues:

• Actual progress bar tracking
• Download safetensors from HF and convert to unquanted GGUF
• Perplexity testing
• Cannot disable llama.cpp update check on startup (fixed in v1.3.1)
• _internal directory required, will see if I can package this into a single exe on the next release (fixed in v1.3.1)
• Custom command line parameters (added in v1.3.0)
• More iMatrix generation parameters (added in v1.3.0)
• Specify multiple KV overrides (added in v1.1.0)
• Better error handling (added in v1.1.0)
• Cannot select output/token embd type (fixed in v1.1.0)
• Importing presets with KV overrides causes UI thread crash (fixed in v1.3.0)

Prerelease issues:

• Base Model label persists even when GGML type is selected

Troubleshooting:

• llama.cpp quantizations errors out with an iostream error: create the quantized_models directory (or set a directory) (fixed in v1.2.1, automatically created on launch)
• SSL module cannot be found error: Install OpenSSL or run from source python src/main.py using the run.bat script (pip install requests)

User interface: