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A backend for LLM's: Important - When installing use the Right install file for the type of GPU you are using.

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TabbyAPI

Python 3.10, 3.11, and 3.12 License: AGPL v3 Discord Server

Developer facing API documentation

Support on Ko-Fi

Important

This is a copy of theroyallab TabbyAPI Git-Readme

Note

Rename the installer - x.js where x is the Graphics card you use to installer.js if unsure use NNVIDIA Cuda 12.x.js (This is the standard one)

Important

In addition to the README, please read the Wiki page for information about getting started!

Note

Need help? Join the Discord Server and get the Tabby role. Please be nice when asking questions.

A FastAPI based application that allows for generating text using an LLM (large language model) using the Exllamav2 backend

Disclaimer

This project is marked rolling release. There may be bugs and changes down the line. Please be aware that you might need to reinstall dependencies if needed.

TabbyAPI is a hobby project solely for a small amount of users. It is not meant to run on production servers. For that, please look at other backends that support those workloads.

Getting Started

Important

This README is not for getting started. Please read the Wiki.

Read the Wiki for more information. It contains user-facing documentation for installation, configuration, sampling, API usage, and so much more.

Supported Model Types

TabbyAPI uses Exllamav2 as a powerful and fast backend for model inference, loading, etc. Therefore, the following types of models are supported:

  • Exl2 (Highly recommended)

  • GPTQ

  • FP16 (using Exllamav2's loader)

In addition, TabbyAPI supports parallel batching using paged attention for Nvidia Ampere GPUs and higher.

Alternative Loaders/Backends

If you want to use a different model type or quantization method than the ones listed above, here are some alternative backends with their own APIs:

Contributing

Use the template when creating issues or pull requests, otherwise the developers may not look at your post.

If you have issues with the project:

  • Describe the issue in detail

  • If you have a feature request, please indicate it as such.

If you have a Pull Request

  • Describe the pull request in detail, what, and why you are changing something

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