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@ -16,7 +16,21 @@ to power Hugging Chat, the Inference API and Inference Endpoint.
</div> </div>
## ## Table of contents
- [Get Started](#get-started)
- [API Documentation](#api-documentation)
- [Using a private or gated model](#using-a-private-or-gated-model)
- [A note on Shared Memory](#a-note-on-shared-memory-shm)
- [Distributed Tracing](#distributed-tracing)
- [Local Install](#local-install)
- [CUDA Kernels](#cuda-kernels)
- [Optimized architectures](#optimized-architectures)
- [Run Falcon](#run-falcon)
- [Run](#run)
- [Quantization](#quantization)
- [Develop](#develop)
- [Testing](#testing)
Text Generation Inference (TGI) is a toolkit for deploying and serving Large Language Models (LLMs). TGI enables high-performance text generation for the most popular open-source LLMs, including Llama, Falcon, StarCoder, BLOOM, GPT-NeoX, and [more](https://huggingface.co/docs/text-generation-inference/supported_models). TGI implements many features, such as: Text Generation Inference (TGI) is a toolkit for deploying and serving Large Language Models (LLMs). TGI enables high-performance text generation for the most popular open-source LLMs, including Llama, Falcon, StarCoder, BLOOM, GPT-NeoX, and [more](https://huggingface.co/docs/text-generation-inference/supported_models). TGI implements many features, such as:
@ -63,19 +77,7 @@ To see all options to serve your models (in the [code](https://github.com/huggin
text-generation-launcher --help text-generation-launcher --help
``` ```
## Optimized architectures ### API documentation
TGI works out of the box to serve optimized models in [this list](https://huggingface.co/docs/text-generation-inference/supported_models).
Other architectures are supported on a best-effort basis using:
`AutoModelForCausalLM.from_pretrained(<model>, device_map="auto")`
or
`AutoModelForSeq2SeqLM.from_pretrained(<model>, device_map="auto")`
## API documentation
You can consult the OpenAPI documentation of the `text-generation-inference` REST API using the `/docs` route. The You can consult the OpenAPI documentation of the `text-generation-inference` REST API using the `/docs` route. The
Swagger UI is also available at: [https://huggingface.github.io/text-generation-inference](https://huggingface.github.io/text-generation-inference). Swagger UI is also available at: [https://huggingface.github.io/text-generation-inference](https://huggingface.github.io/text-generation-inference).
@ -164,6 +166,20 @@ the kernels by using the `DISABLE_CUSTOM_KERNELS=True` environment variable.
Be aware that the official Docker image has them enabled by default. Be aware that the official Docker image has them enabled by default.
## Optimized architectures
TGI works out of the box to serve optimized models in [this list](https://huggingface.co/docs/text-generation-inference/supported_models).
Other architectures are supported on a best-effort basis using:
`AutoModelForCausalLM.from_pretrained(<model>, device_map="auto")`
or
`AutoModelForSeq2SeqLM.from_pretrained(<model>, device_map="auto")`
## Run Falcon ## Run Falcon
### Run ### Run