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README.md
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README.md
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# AutoGGUF - automated GGUF model quantizer
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# AutoGGUF - automated GGUF model quantizer
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AutoGGUF provides a graphical user interface for quantizing GGUF models
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[](https://github.com/ggerganov/llama.cpp)
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using the llama.cpp library. It allows users to download different versions of
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llama.cpp, manage multiple backends, and perform quantization tasks with various
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options.
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## Features:
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AutoGGUF 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.
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1. Download and manage llama.cpp backends
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2. Select and quantize GGUF models
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3. Configure quantization parameters
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4. Monitor system resources during quantization
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## Usage:
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## Features
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**Cross platform**:
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- Download and manage llama.cpp backends
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1. Install dependencies, either using the `requirements.txt` file or `pip install PyQt6 requests psutil`.
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- Select and quantize GGUF models
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2. Run the `run.bat` script to start the application, or run the command `python src/main.py`.
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- Configure quantization parameters
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- Monitor system resources during quantization
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**Windows**:
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## Usage
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1. Download latest release, extract all to folder and run `AutoGGUF.exe`
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2. Enjoy!
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## Building:
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### Cross-platform
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1. Install dependencies:
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```
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pip install -r requirements.txt
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```
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or
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```
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pip install PyQt6 requests psutil shutil
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```
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2. Run the application:
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```
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python src/main.py
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```
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or use the `run.bat` script.
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**Cross platform**:
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### Windows
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1. Download the latest release
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2. Extract all files to a folder
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3. Run `AutoGGUF.exe`
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## Building
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### Cross-platform
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```bash
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```bash
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cd src
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cd src
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pip install -U pyinstaller
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pip install -U pyinstaller
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@ -33,56 +52,55 @@ ## Building:
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cd dist/main
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cd dist/main
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./main
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./main
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```
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```
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**Windows**:
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### Windows
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```bash
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```bash
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build RELEASE/DEV
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build RELEASE/DEV
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```
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```
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Find exe in `build/<type>/dist/AutoGGUF.exe`.
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Find the executable in `build/<type>/dist/AutoGGUF.exe`.
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## Dependencies
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## Dependencies:
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- PyQt6
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- PyQt6
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- requests
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- requests
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- psutil
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- psutil
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- shutil
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- shutil
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- OpenSSL
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- OpenSSL
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## Localizations:
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## Localizations
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View the list of languages supported at [AutoGGUF/wiki/Installation#configuration](https://github.com/leafspark/AutoGGUF/wiki/Installation#configuration) (LLM translated, except for English)
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View the list of supported languages at [AutoGGUF/wiki/Installation#configuration](https://github.com/leafspark/AutoGGUF/wiki/Installation#configuration) (LLM translated, except for English).
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In order to use them, please set the `AUTOGGUF_LANGUAGE` environment variable to one of the listed language codes.
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To use a specific language, set the `AUTOGGUF_LANGUAGE` environment variable to one of the listed language codes.
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## Known Issues
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## Issues:
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- Saving preset while quantizing causes UI thread crash (planned fix: remove this feature)
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- Saving preset while quantizing causes UI thread crash (planned fix: remove this feature)
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- Cannot delete task while processing, you must cancel it first or the program crashes (planned fix: don't allow deletion before cancelling, or cancel automatically)
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- Cannot delete task while processing (planned fix: disallow deletion before cancelling or cancel automatically)
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- Base Model text still shows when GGML is selected as LoRA type (fix: include text in show/hide Qt layout)
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- Base Model text still shows when GGML is selected as LoRA type (fix: include text in show/hide Qt layout)
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- ~~Cannot disable llama.cpp update check on startup~~ (fixed in v1.3.1)
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- ~~`_internal` directory required, will see if I can package this into a single exe on the next release~~ (fixed in v1.3.1)
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- ~~Custom command line parameters~~ (added in v1.3.0)
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- ~~More iMatrix generation parameters~~ (added in v1.3.0)
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- ~~Specify multiple KV overrides~~ (added in v1.1.0)
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- ~~Better error handling~~ (added in v1.1.0)
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- ~~Cannot select output/token embd type~~ (fixed in v1.1.0)
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- ~~Importing presets with KV overrides causes UI thread crash~~ (fixed in v1.3.0)
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## Planned features:
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## Planned Features
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- Actual progress bar tracking
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- Actual progress bar tracking
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- Download safetensors from HF and convert to unquanted GGUF
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- Download safetensors from HF and convert to unquantized GGUF
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- Perplexity testing
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- Perplexity testing
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- Managing shards (coming in the next release)
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- Managing shards (coming in the next release)
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- Time estimated for quantization
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- Time estimation for quantization
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- Dynamic values for KV cache, e.g. autogguf.quantized.time=str:{system.time.milliseconds} (coming in the next release)
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- Dynamic values for KV cache (coming in the next release)
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- Ability to select and start multiple quants at once (saved in presets) (coming in the next release)
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- Ability to select and start multiple quants at once (saved in presets, coming in the next release)
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## Troubleshooting:
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## Troubleshooting
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- ~~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)
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- SSL module cannot be found error: Install OpenSSL or run from source `python src/main.py` using the `run.bat` script (`pip install requests`)
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## Contributing:
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- SSL module cannot be found error: Install OpenSSL or run from source using `python src/main.py` with the `run.bat` script (`pip install requests`)
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Simply fork the repo and make your changes; when merging make sure to have the latest commits. Description should contain a changelog of what's new.
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## Contributing
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Fork the repo, make your changes, and ensure you have the latest commits when merging. Include a changelog of new features in your pull request description.
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## User Interface
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## User interface:
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## Stargazers:
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## Stargazers
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[](https://star-history.com/#leafspark/AutoGGUF&Date)
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[](https://star-history.com/#leafspark/AutoGGUF&Date)
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