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GGUF (Groovy GGUF Utility Functions)

GGUF is a powerful bash script for managing and interacting with large language models using llama.cpp. It provides a comprehensive set of functions for downloading, running, and chatting with AI models, as well as managing a local database of model information.

🚀 Features

  • Download models from Hugging Face
  • Run models and start server instances
  • Interactive chat sessions with models
  • Manage a local database of model information
  • Generate embeddings
  • Tokenize and detokenize text
  • Monitor running model servers
  • Fetch recent and trending GGUF models from Hugging Face

gguf

📋 Prerequisites

Before you begin, ensure you have the following installed:

  • llama-server command (macOS: brew install llama.cpp)
  • huggingface-cli command (macOS: brew install huggingface-cli)
  • sqlite3 (usually pre-installed on macOS)
  • jq (macOS: brew install jq)

🛠 Installation

  1. Clone this repository:

    git clone https://github.com/garyblankenship/gguf.git
    
  2. Make the script executable:

    chmod +x gguf.sh
    
  3. Optionally, add the script to your PATH for easier access.

🎮 Usage

Here are some common commands:

# Download a new model
gguf pull bartowski/Qwen2.5-Math-1.5B-Instruct-GGUF

# List all models
gguf ls

# Start a chat session with a model
gguf chat model-slug

# Generate embeddings
gguf embed model-slug "Your text here"

# Check server health
gguf health

# Show running processes
gguf ps

# Get recent GGUF models from Hugging Face
gguf recent

# Get trending GGUF models from Hugging Face
gguf trending

For a full list of commands, run:

gguf

For help with a specific command, use:

gguf <command> --help

📚 Documentation

For more detailed information about each command and its options, please refer to the inline comments in the script or use the --help option with any command.

🤝 Contributing

Contributions, issues, and feature requests are welcome! Feel free to check the issues page.

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgements

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Shell script inspired by Ollama.

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