Tabby is a developer tool for running and managing local AI models, built on the llama.cpp engine for efficient local inference. This setup allows developers to work with large language models directly on their machines without heavy cloud dependencies. The tool emphasizes practical configuration for everyday use.

Developers can control where Tabby stores cached model files using the TABBY_MODEL_CACHE_ROOT environment variable. This is crucial for managing disk space, placing models on faster drives, or standardizing paths across development environments. The model registry is publicly available on GitHub for reference and transparency.

For authenticated access, users generate an access token after a one-time browser-based account setup. Checking the token involves logging into the service and navigating account settings. This workflow balances local execution with the need for managed services and model distribution.