From 4d128409864a26410814754c19e49e342196fbbe Mon Sep 17 00:00:00 2001 From: Merve Noyan Date: Thu, 7 Sep 2023 15:25:54 +0200 Subject: [PATCH] Update docs/source/basic_tutorials/non_core_models.md Co-authored-by: Pedro Cuenca --- docs/source/basic_tutorials/non_core_models.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/basic_tutorials/non_core_models.md b/docs/source/basic_tutorials/non_core_models.md index 324dc930..b60c5c3d 100644 --- a/docs/source/basic_tutorials/non_core_models.md +++ b/docs/source/basic_tutorials/non_core_models.md @@ -2,7 +2,7 @@ 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