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