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Mac M1/M2 (Preview)

Thanks to Apple's Accelerate and CoreML frameworks, we can now run Tabby on edge devices with reasonable inference speed. Follow the steps below to set it up:

  1. Download the tabby binary from the latest Release page, rename it to tabby, place it in a directory included in your $PATH variable, and ensure its permissions are set to executable (e.g., 755).

  2. Run tabby --help to verify successful installation.

  3. Start the server with:

tabby serve --model TabbyML/T5P-220M

:::tip The compute power of M1/M2 is limited and is likely to be sufficient only for individual usage. If you require a shared instance for a team, we recommend considering Docker hosting with CUDA. You can find more information about Docker here.