2.7 KiB
2.7 KiB
--8<-- [start:requirements]
- GPU: Validated on gfx942 (It should be supported on the AMD GPUs that are supported by vLLM.)
--8<-- [end:requirements]
--8<-- [start:set-up-using-python]
vLLM-Omni current recommends the steps in under setup through Docker Images.
--8<-- [start:pre-built-wheels]
--8<-- [end:pre-built-wheels]
--8<-- [start:build-wheel-from-source]
--8<-- [end:build-wheel-from-source]
--8<-- [start:build-docker]
Build docker image
DOCKER_BUILDKIT=1 docker build -f docker/Dockerfile.rocm -t vllm-omni-rocm .
Launch the docker image
Launch with OpenAI API Server
docker run --rm \
--group-add=video \
--ipc=host \
--cap-add=SYS_PTRACE \
--security-opt seccomp=unconfined \
--device /dev/kfd \
--device /dev/dri \
-v ~/.cache/huggingface:/root/.cache/huggingface \
--env "HF_TOKEN=$HF_TOKEN" \
-p 8091:8091 \
--ipc=host \
vllm-omni-rocm \
--model Qwen/Qwen3-Omni-30B-A3B-Instruct --port 8091
Launch with interactive session for development
docker run --rm -it \
--network=host \
--group-add=video \
--ipc=host \
--cap-add=SYS_PTRACE \
--security-opt seccomp=unconfined \
--device /dev/kfd \
--device /dev/dri \
-v <path/to/model>:/app/model \
-v ~/.cache/huggingface:/root/.cache/huggingface \
--entrypoint bash \
vllm-omni-rocm
--8<-- [end:build-docker]
--8<-- [start:pre-built-images]
vLLM-Omni offers an official docker image for deployment. These images are built on top of vLLM docker images and available on Docker Hub as vllm/vllm-omni-rocm. The version of vLLM-Omni indicates which release of vLLM it is based on.
Launch vLLM-Omni Server
Here's an example deployment command that has been verified on 2 x MI300's:
docker run --rm \
--group-add=video \
--ipc=host \
--cap-add=SYS_PTRACE \
--security-opt seccomp=unconfined \
--device /dev/kfd \
--device /dev/dri \
-v <path/to/model>:/app/model \
-v ~/.cache/huggingface:/root/.cache/huggingface \
--env "HF_TOKEN=$HF_TOKEN" \
-p 8091:8091 \
vllm/vllm-omni-rocm:v0.14.0rc1 \
--model Qwen/Qwen3-Omni-30B-A3B-Instruct --omni --port 8091
Launch an interactive terminal with prebuilt docker image.
If you want to run in dev environment you can launch the docker image as follows:
docker run --rm -it \
--network=host \
--group-add=video \
--ipc=host \
--cap-add=SYS_PTRACE \
--security-opt seccomp=unconfined \
--device /dev/kfd \
--device /dev/dri \
-v <path/to/model>:/app/model \
-v ~/.cache/huggingface:/root/.cache/huggingface \
--env "HF_TOKEN=$HF_TOKEN" \
--entrypoint bash \
vllm/vllm-omni-rocm:v0.14.0rc1