mirror of https://github.com/leafspark/AutoGGUF
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.github/workflows | ||
assets | ||
src | ||
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CONTRIBUTING.md | ||
LICENSE | ||
README.md | ||
build.bat | ||
requirements.txt | ||
run.bat |
README.md
AutoGGUF - automated GGUF model quantizer
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.
Features
- Download and manage llama.cpp backends
- Select and quantize GGUF models
- Configure quantization parameters
- Monitor system resources during quantization
Usage
Cross-platform
- Install dependencies:
orpip install -r requirements.txt
pip install PyQt6 requests psutil shutil
- Run the application:
or use thepython src/main.py
run.bat
script.
Windows
- Download the latest release
- Extract all files to a folder
- Run
AutoGGUF.exe
Building
Cross-platform
cd src
pip install -U pyinstaller
pyinstaller main.py --onefile
cd dist/main
./main
Windows
build RELEASE/DEV
Find the executable in build/<type>/dist/AutoGGUF.exe
.
Dependencies
- PyQt6
- requests
- psutil
- shutil
- OpenSSL
Localizations
View the list of supported languages at AutoGGUF/wiki/Installation#configuration (LLM translated, except for English).
To use a specific language, set the AUTOGGUF_LANGUAGE
environment variable to one of the listed language codes.
Known Issues
- Saving preset while quantizing causes UI thread crash (planned fix: remove this feature)
- Cannot delete task while processing (planned fix: disallow deletion before cancelling or cancel automatically)
- Base Model text still shows when GGML is selected as LoRA type (fix: include text in show/hide Qt layout)
Planned Features
- Actual progress bar tracking
- Download safetensors from HF and convert to unquantized GGUF
- Perplexity testing
- Managing shards (coming in the next release)
- Time estimation for quantization
- Dynamic values for KV cache (coming in the next release)
- Ability to select and start multiple quants at once (saved in presets, coming in the next release)
Troubleshooting
- SSL module cannot be found error: Install OpenSSL or run from source using
python src/main.py
with therun.bat
script (pip install requests
)
Contributing
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.