LlamaChat

LlamaChat is a locally-run chat application for macOS that lets you interact with open-source LLaMA-family models (LLaMA, Alpaca, Vicuna, GPT4All, etc.) directly on your Mac. It supports importing raw PyTorch model checkpoints or pre-converted .ggml model files, running entirely offline with no cloud dependency. The project emphasizes open-source accessibility, model interoperability, and local processing.

How to Use LlamaChat

1. Install on macOS. Download the app or install via Homebrew: brew install --cask llamachat (requires macOS 13 and a compatible processor).
2. Choose a model. Select from available locally-presented models (e.g., LLaMA, Alpaca, Vicuna, GPT4All) that you have integrated or imported.
3. Import model files. Import raw published PyTorch checkpoints or pre-converted .ggml model files into LlamaChat.
4. Chat locally. Start chatting with the selected model directly on your Mac.

Note: LlamaChat does not include any model files by default. You are responsible for acquiring and integrating the appropriate model files in accordance with each provider’s terms.

Features

• Local-first chat with LLaMA-family models (LLaMA, Alpaca, Vicuna, GPT4All, and more coming soon)
• Import support for raw PyTorch checkpoints and .ggml model files
• Fully open-source foundation (llama.cpp and llama.swift) and free to use
• Cross-processor compatibility (Apple Silicon and Intel; macOS 13+)
• Independent of any model provider partnerships or cloud services
• Clear licensing and attribution handling for models used

How It Works

• LlamaChat leverages open-source libraries (llama.cpp, llama.swift) to run large language models locally.
• Users bring their own model files; the app provides a UI to load and interact with these models.
• The software is designed to be100% free and open-source, with ongoing community contributions.

Safety and Legal Considerations

• You are responsible for obtaining and using models in compliance with their licenses and terms.
• As an independent application, LlamaChat is not affiliated with or endorsed by Meta Platforms, Stanford, Nomic AI, or other entities mentioned in the project notes.

Core Features

• Local, offline execution of LLaMA-family models on macOS
• Import both PyTorch checkpoints and .ggml model files
• Open-source, freely available under the project licenses
• Compatibility with Apple Silicon and Intel Macs (macOS 13+)
• No bundled models; user-provided models only
• Simple, self-contained setup with community-driven development