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kingbri d2c6ae2d35 API: Back to async 
According to FastAPI docs, if you're using a generic function, running
it in async will make it more performant (which makes sense since
running def functions for routes will automatically run the caller
through a threadpool).

Tested and everything works fine.

Signed-off-by: kingbri <bdashore3@proton.me>
2024-03-04 23:21:40 -05:00
.github Create pull request template 2024-02-09 14:53:29 -05:00
backends/exllamav2 API: Add more methods to semaphore 2024-03-04 23:21:40 -05:00
colab Tree: Refactor code organization 2024-01-25 00:15:40 -05:00
common API: Back to async 2024-03-04 23:21:40 -05:00
docker Tree: Refactor code organization 2024-01-25 00:15:40 -05:00
loras Implement lora support (#24) 2023-12-08 23:38:08 -05:00
models Tree: Update documentation and configs 2023-11-16 02:30:33 -05:00
OAI API: Add more methods to semaphore 2024-03-04 23:21:40 -05:00
sampler_overrides Neutralize samplers (#59) 2024-02-08 00:23:09 -05:00
templates Templates: Update folder 2023-12-18 23:53:47 -05:00
tests Tree: Refactor code organization 2024-01-25 00:15:40 -05:00
.gitignore Tree: Unify sampler parameters and add override support 2024-01-25 00:15:40 -05:00
.ruff.toml feat: workflows for formatting/linting (#35) 2023-12-22 16:20:35 +00:00
config_sample.yml Additional clarification for override_base_seq_len 2024-03-02 09:29:50 -08:00
formatting.bat feat: workflows for formatting/linting (#35) 2023-12-22 16:20:35 +00:00
formatting.sh feat: workflows for formatting/linting (#35) 2023-12-22 16:20:35 +00:00
LICENSE Create LICENSE 2023-11-16 17:43:23 -05:00
main.py API: Back to async 2024-03-04 23:21:40 -05:00
README.md Update README 2024-02-20 00:19:31 -05:00
requirements-amd.txt Requirements: Bump ExllamaV2 2024-02-24 12:26:08 -05:00
requirements-cu118.txt Requirements: Bump ExllamaV2 2024-02-24 12:26:08 -05:00
requirements-dev.txt feat: workflows for formatting/linting (#35) 2023-12-22 16:20:35 +00:00
requirements-nowheel.txt feat: logging (#39) 2023-12-23 04:33:31 +00:00
requirements.txt Requirements: Bump ExllamaV2 2024-02-24 12:26:08 -05:00
start.bat Tree: Format and cleanup start 2023-12-27 01:17:31 -05:00
start.py Tree: Refactor code organization 2024-01-25 00:15:40 -05:00
start.sh Start: Add shell script 2023-12-27 23:53:14 -05:00

README.md

TabbyAPI

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

Getting Started

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)

Alternative Loaders/Backends

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

Contributing

If you have issues with the project:

  • Describe the issues 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

Developers and Permissions

Creators/Developers: