Unverified Commit 24704191 authored by Kay Yan's avatar Kay Yan Committed by GitHub
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[Docs] Fix the outdated URL for installing from vLLM binaries (#21523)


Signed-off-by: default avatarKay Yan <kay.yan@daocloud.io>
Co-authored-by: default avatarHarry Mellor <19981378+hmellor@users.noreply.github.com>
parent 61a6905a
...@@ -57,8 +57,7 @@ cc the PyTorch release team to initiate discussion on how to address them. ...@@ -57,8 +57,7 @@ cc the PyTorch release team to initiate discussion on how to address them.
## Update CUDA version ## Update CUDA version
The PyTorch release matrix includes both stable and experimental [CUDA versions](https://github.com/pytorch/pytorch/blob/main/RELEASE.md#release-compatibility-matrix). Due to limitations, only the latest stable CUDA version (for example, The PyTorch release matrix includes both stable and experimental [CUDA versions](https://github.com/pytorch/pytorch/blob/main/RELEASE.md#release-compatibility-matrix). Due to limitations, only the latest stable CUDA version (for example, torch `2.7.1+cu126`) is uploaded to PyPI. However, vLLM may require a different CUDA version,
`torch2.7.0+cu12.6`) is uploaded to PyPI. However, vLLM may require a different CUDA version,
such as 12.8 for Blackwell support. such as 12.8 for Blackwell support.
This complicates the process as we cannot use the out-of-the-box This complicates the process as we cannot use the out-of-the-box
`pip install torch torchvision torchaudio` command. The solution is to use `pip install torch torchvision torchaudio` command. The solution is to use
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...@@ -38,10 +38,10 @@ We recommend leveraging `uv` to [automatically select the appropriate PyTorch in ...@@ -38,10 +38,10 @@ We recommend leveraging `uv` to [automatically select the appropriate PyTorch in
As of now, vLLM's binaries are compiled with CUDA 12.8 and public PyTorch release versions by default. We also provide vLLM binaries compiled with CUDA 12.6, 11.8, and public PyTorch release versions: As of now, vLLM's binaries are compiled with CUDA 12.8 and public PyTorch release versions by default. We also provide vLLM binaries compiled with CUDA 12.6, 11.8, and public PyTorch release versions:
```bash ```bash
# Install vLLM with CUDA 11.8. # Install vLLM with a specific CUDA version (e.g., 11.8 or 12.6).
export VLLM_VERSION=0.6.1.post1 export VLLM_VERSION=$(curl -s https://api.github.com/repos/vllm-project/vllm/releases/latest | jq -r .tag_name | sed 's/^v//')
export PYTHON_VERSION=312 export CUDA_VERSION=118 # or 126
uv pip install https://github.com/vllm-project/vllm/releases/download/v${VLLM_VERSION}/vllm-${VLLM_VERSION}+cu118-cp${PYTHON_VERSION}-cp${PYTHON_VERSION}-manylinux1_x86_64.whl --extra-index-url https://download.pytorch.org/whl/cu118 uv pip install https://github.com/vllm-project/vllm/releases/download/v${VLLM_VERSION}/vllm-${VLLM_VERSION}+cu${CUDA_VERSION}-cp38-abi3-manylinux1_x86_64.whl --extra-index-url https://download.pytorch.org/whl/cu${CUDA_VERSION}
``` ```
[](){ #install-the-latest-code } [](){ #install-the-latest-code }
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