Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot. It boasts several key features:

• Self-contained, with no need for a DBMS or cloud service.
• OpenAPI interface, easy to integrate with existing infrastructure (e.g Cloud IDE).
• Supports consumer-grade GPUs.

• 09/21/2023 We've hit 10K stars 🌟 on GitHub! 🚀🎉👏
• 09/18/2023 Apple's M1/M2 Metal inference support has landed in v0.1.1!
• 08/31/2023 Tabby's first stable release v0.0.1 🥳.

The easiest way to start a Tabby server is by using the following Docker command:

docker run -it \
  --gpus all -p 8080:8080 -v $HOME/.tabby:/data \
  tabbyml/tabby \
  serve --model TabbyML/SantaCoder-1B --device cuda

For additional options (e.g inference type, parallelism), please refer to the documentation at https://tabbyml.github.io/tabby.

git clone --recurse-submodules https://github.com/TabbyML/tabby
cd tabby

If you have already cloned the repository, you could run the git submodule update --recursive --init command to fetch all submodules.

1. Set up the Rust environment by following this tutorial.

2. Install the required dependencies:

# For MacOS
brew install protobuf

# For Ubuntu / Debian
apt-get install protobuf-compiler libopenblas-dev

3. Now, you can build Tabby by running the command cargo build.

... and don't forget to submit a Pull Request