![AutoGGUF-banner](https://github.com/user-attachments/assets/0f74b104-0541-46a7-9ac8-4a3fcb74b896) # AutoGGUF - automated GGUF model quantizer [![Powered by llama.cpp](https://img.shields.io/badge/Powered%20by-llama.cpp-green.svg)](https://github.com/ggerganov/llama.cpp) ![GitHub release](https://img.shields.io/github/release/leafspark/AutoGGUF.svg) ![GitHub last commit](https://img.shields.io/github/last-commit/leafspark/AutoGGUF.svg) ![GitHub stars](https://img.shields.io/github/stars/leafspark/AutoGGUF.svg) ![GitHub forks](https://img.shields.io/github/forks/leafspark/AutoGGUF.svg) ![GitHub top language](https://img.shields.io/github/languages/top/leafspark/AutoGGUF.svg) ![GitHub repo size](https://img.shields.io/github/repo-size/leafspark/AutoGGUF.svg) ![GitHub license](https://img.shields.io/github/license/leafspark/AutoGGUF.svg) 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 1. Install dependencies: ``` pip install -r requirements.txt ``` or ``` pip install PyQt6 requests psutil shutil ``` 2. Run the application: ``` python src/main.py ``` or use the `run.bat` script. ### Windows 1. Download the latest release 2. Extract all files to a folder 3. Run `AutoGGUF.exe` ## Building ### Cross-platform ```bash cd src pip install -U pyinstaller pyinstaller main.py --onefile cd dist/main ./main ``` ### Windows ```bash build RELEASE/DEV ``` Find the executable in `build//dist/AutoGGUF.exe`. ## Dependencies - PyQt6 - requests - psutil - shutil - OpenSSL ## Localizations View the list of supported languages at [AutoGGUF/wiki/Installation#configuration](https://github.com/leafspark/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 the `run.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. ## User Interface ![image](https://github.com/user-attachments/assets/2660c841-07ba-4c3f-ae3a-e63c7068bdc1) ## Stargazers [![Star History Chart](https://api.star-history.com/svg?repos=leafspark/AutoGGUF&type=Date)](https://star-history.com/#leafspark/AutoGGUF&Date)