[Rebase] Rebase to vllm 0.28.0 (#6606)
Signed-off-by: tzhouam <tzhouam@connect.ust.hk> Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
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@@ -19,10 +19,10 @@ uv venv --python 3.12 --seed
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source .venv/bin/activate
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# On CUDA
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uv pip install vllm==0.26.0 --torch-backend=auto
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uv pip install vllm==0.28.0 --torch-backend=auto
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# On ROCm
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uv pip install vllm==0.26.0+rocm723 --extra-index-url https://wheels.vllm.ai/rocm/0.26.0/rocm723
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uv pip install vllm==0.28.0+rocm723 --extra-index-url https://wheels.vllm.ai/rocm/0.28.0/rocm723
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git clone https://github.com/vllm-project/vllm-omni.git
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cd vllm-omni
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@@ -34,7 +34,7 @@ For additional installation methods — please see the [installation guide](inst
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!!! note
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It is important to install the same major & minor version of vLLM and vLLM Omni, otherwise things may not work as expected. If the versions are misaligned, you will see a warning when you import vLLM Omni.
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If you are seeing strange behavior with the `vllm` command not handling the `--omni` flag correctly, you most likely have a version mismatch with vLLM < `0.26.0` and vLLM Omni `0.26.0`, as vLLM Omni no longer hijacks the vLLM entrypoint. Updating vLLM should resolve this issue.
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If you are seeing strange behavior with the `vllm` command not handling the `--omni` flag correctly, you most likely have a version mismatch with vLLM < `0.28.0` and vLLM Omni `0.28.0`, as vLLM Omni no longer hijacks the vLLM entrypoint. Updating vLLM should resolve this issue.
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## Offline Inference
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