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Update docs/source/basic_tutorials/non_core_models.md

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Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
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Merve Noyan 2023-09-07 15:25:54 +02:00 committed by GitHub
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docs/source/basic_tutorials/non_core_models.md
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TGI supports various LLM architectures (see full list [here](../supported_models)). If you wish to serve a model that is not one of the supported models, TGI will fallback to the `transformers` implementation of that model. This means you will be unable to use some of the features introduced by TGI, such as tensor-parallel sharding or flash attention. However, you can still get many benefits of TGI, such as continuous batching or streaming outputs.
You can serve these models using Docker like below 👇
You can serve these models using the same Docker command-line invocation as with fully supported models 👇
```bash
docker run --gpus all --shm-size 1g -p 8080:80 -v $volume:/data ghcr.io/huggingface/text-generation-inference:latest --model-id gpt2