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README.md

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@@ -144,8 +144,8 @@ Once you have the model repository set up, it is time to launch the Triton serve
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We will use the [pre-built Triton container with vLLM backend](#option-1-use-the-pre-built-docker-container) from
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[NGC](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/tritonserver) in this example.
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Run the following command inside the vllm_backend directory:
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```
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# cd into vllm_backend directory
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docker run --gpus all -it --net=host --rm -p 8001:8001 --shm-size=1G --ulimit memlock=-1 --ulimit stack=67108864 -v ${PWD}:/work -w /work nvcr.io/nvidia/tritonserver:<xx.yy>-vllm-python-py3 tritonserver --model-repository ./samples/model_repository
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```
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