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
• Parallel quantization + imatrix generation
• LoRA conversion and merging

Usage

Cross-platform

1. Install dependencies:

   pip install -r requirements.txt
   

   or

   pip install PyQt6 requests psutil shutil numpy torch safetensors gguf
   

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

Verifying Releases

Linux/macOS:

gpg --import AutoGGUF-v1.5.0-prerel.asc
gpg --verify AutoGGUF-v1.5.0-Windows-avx2-prerel.zip.sig AutoGGUF-v1.5.0-Windows-avx2-prerel.zip
sha256sum -c AutoGGUF-v1.5.0-prerel.sha256

Windows (PowerShell):

# Import the public key
gpg --import AutoGGUF-v1.5.0-prerel.asc

# Verify the signature
gpg --verify AutoGGUF-v1.5.0-Windows-avx2-prerel.zip.sig AutoGGUF-v1.5.0-Windows-avx2-prerel.zip

# Check SHA256
$fileHash = (Get-FileHash -Algorithm SHA256 AutoGGUF-v1.5.0-Windows-avx2-prerel.zip).Hash.ToLower()
$storedHash = (Get-Content AutoGGUF-v1.5.0-prerel.sha256 | Select-String AutoGGUF-v1.5.0-Windows-avx2-prerel.zip).Line.Split()[0]
if ($fileHash -eq $storedHash) { "SHA256 Match" } else { "SHA256 Mismatch" }

Release keys are identical to ones used for commiting.

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
• psutil
• shutil
• numpy
• torch
• safetensors
• gguf (bundled)

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 (note: some languages may not be fully supported yet, those will fallback to English).

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)

Planned Features

• Actual progress bar tracking
• Perplexity testing
• Time estimation for quantization

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. Read CONTRIBUTING.md for more information.

User Interface

Stargazers