mirror of https://github.com/leafspark/AutoGGUF
149 lines
5.4 KiB
Markdown
149 lines
5.4 KiB
Markdown
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# AutoGGUF - automated GGUF model quantizer
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<!-- Project Status -->
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[](https://github.com/leafspark/AutoGGUF/releases)
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[](https://github.com/leafspark/AutoGGUF/commits)
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[]()
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<!-- Project Info -->
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[](https://github.com/ggerganov/llama.cpp)
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[]()
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[](https://github.com/leafspark/AutoGGUF/blob/main/LICENSE)
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<!-- Repository Stats -->
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<!-- Contribution -->
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[](https://github.com/psf/black)
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[](https://github.com/leafspark/AutoGGUF/issues)
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[](https://github.com/leafspark/AutoGGUF/pulls)
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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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- Parallel quantization + imatrix generation
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- LoRA conversion and merging
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- Preset saving and loading
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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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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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Standard builds:
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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-x64.exe`
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Setup builds:
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1. Download setup varient of latest release
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2. Extract all files to a folder
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3. Run the setup program
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4. The .GGUF extension will be registered with the program automatically
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5. Run the program from the Start Menu or desktop shortcuts
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### Verifying Releases
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#### Linux/macOS:
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```bash
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gpg --import AutoGGUF-v1.5.0-prerel.asc
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gpg --verify AutoGGUF-v1.5.0-Windows-avx2-prerel.zip.sig AutoGGUF-v1.5.0-Windows-avx2-prerel.zip
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sha256sum -c AutoGGUF-v1.5.0-prerel.sha256
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```
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#### Windows (PowerShell):
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```powershell
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# Import the public key
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gpg --import AutoGGUF-v1.5.0-prerel.asc
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# Verify the signature
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gpg --verify AutoGGUF-v1.5.0-Windows-avx2-prerel.zip.sig AutoGGUF-v1.5.0-Windows-avx2-prerel.zip
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# Check SHA256
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$fileHash = (Get-FileHash -Algorithm SHA256 AutoGGUF-v1.5.0-Windows-avx2-prerel.zip).Hash.ToLower()
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$storedHash = (Get-Content AutoGGUF-v1.5.0-prerel.sha256 | Select-String AutoGGUF-v1.5.0-Windows-avx2-prerel.zip).Line.Split()[0]
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if ($fileHash -eq $storedHash) { "SHA256 Match" } else { "SHA256 Mismatch" }
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```
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Release keys are identical to ones used for commiting.
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## Building
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### Cross-platform
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```bash
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pip install -U pyinstaller
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./build.sh RELEASE | DEV
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cd build/<type>/dist/
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./AutoGGUF
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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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You can also use the slower build but faster executable script (Nuitka):
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```bash
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build_optimized RELEASE | DEV
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```
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## Dependencies
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Find them in `requirements.txt`.
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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 (note: some languages may not be fully supported yet, those will fall back to English).
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## Known Issues
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- None!
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## Planned Features
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- Time estimation for quantization
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- Actual progress bar tracking
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- Perplexity testing
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- Web API and management (partially implemented in v1.6.2)
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- HuggingFace upload/download (coming in the next release)
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- AutoFP8 quantization and bitsandbytes (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. Read `CONTRIBUTING.md` for more information.
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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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