Unsupported model serving docs (#906)
Co-authored-by: Omar Sanseviero <osanseviero@gmail.com> Co-authored-by: Mishig <mishig.davaadorj@coloradocollege.edu> Co-authored-by: Pedro Cuenca <pedro@huggingface.co> Co-authored-by: OlivierDehaene <olivier@huggingface.co>
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title: Serving Private & Gated Models
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- local: basic_tutorials/using_cli
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title: Using TGI CLI
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- local: basic_tutorials/non_core_models
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title: Non-core Model Serving
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title: Tutorials
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- sections:
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- local: conceptual/streaming
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# Non-core Model Serving
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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.
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You can serve these models using the same Docker command-line invocation as with fully supported models 👇
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```bash
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docker run --gpus all --shm-size 1g -p 8080:80 -v $volume:/data ghcr.io/huggingface/text-generation-inference:latest --model-id gpt2
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```
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If the model you wish to serve is a custom transformers model, and its weights and implementation are available in the Hub, you can still serve the model by passing the `--trust-remote-code` flag to the `docker run` command like below 👇
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```bash
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docker run --gpus all --shm-size 1g -p 8080:80 -v $volume:/data ghcr.io/huggingface/text-generation-inference:latest --model-id <CUSTOM_MODEL_ID> --trust-remote-code
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```
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Finally, if the model is not on Hugging Face Hub but on your local, you can pass the path to the folder that contains your model like below 👇
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```bash
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# Make sure your model is in the $volume directory
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docker run --shm-size 1g -p 8080:80 -v $volume:/data ghcr.io/huggingface/text-generation-inference:latest --model-id /data/<PATH-TO-FOLDER>
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```
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You can refer to [transformers docs on custom models](https://huggingface.co/docs/transformers/main/en/custom_models) for more information.
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