mirror of https://github.com/leafspark/AutoGGUF
107 lines
3.6 KiB
Markdown
107 lines
3.6 KiB
Markdown
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# AutoGGUF - automated GGUF model quantizer
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[](https://github.com/ggerganov/llama.cpp)
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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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## Features
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- Download and manage llama.cpp backends
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- Select and quantize GGUF models
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- Configure quantization parameters
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- Monitor system resources during quantization
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## Usage
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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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### 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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cd src
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pip install -U pyinstaller
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pyinstaller main.py --onefile
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cd dist/main
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./main
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```
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### Windows
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```bash
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build RELEASE/DEV
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```
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Find the executable in `build/<type>/dist/AutoGGUF.exe`.
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## Dependencies
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- PyQt6
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- requests
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- psutil
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- shutil
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- OpenSSL
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## Localizations
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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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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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- Saving preset while quantizing causes UI thread crash (planned fix: remove this feature)
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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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## Planned Features
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- Actual progress bar tracking
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- Download safetensors from HF and convert to unquantized GGUF
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- Perplexity testing
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- Managing shards (coming in the next release)
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- Time estimation for quantization
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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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## Troubleshooting
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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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## 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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## Stargazers
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[](https://star-history.com/#leafspark/AutoGGUF&Date)
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