Update Install Method 2. From source (#2232)
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# Usage (to build SGLang ROCm docker image):
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# Usage (to build SGLang ROCm docker image):
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# docker build --build-arg SGL_BRANCH=v0.3.6.post2 -t testImage -f Dockerfile.rocm .
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# docker build --build-arg SGL_BRANCH=v0.3.6.post2 -t v0.3.6.post2-rocm620 -f Dockerfile.rocm .
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# default base image
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# default base image
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ARG BASE_IMAGE="rocm/vllm-dev:20241022"
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ARG BASE_IMAGE="rocm/vllm-dev:20241022"
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@@ -28,6 +28,17 @@ pip install flashinfer -i https://flashinfer.ai/whl/cu121/torch2.4/
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Note: Please check the [FlashInfer installation doc](https://docs.flashinfer.ai/installation.html) to install the proper version according to your PyTorch and CUDA versions.
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Note: Please check the [FlashInfer installation doc](https://docs.flashinfer.ai/installation.html) to install the proper version according to your PyTorch and CUDA versions.
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Note: To AMD ROCm system with Instinct/MI GPUs, do following instead:
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```
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# Use the last release branch
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git clone -b v0.3.6.post2 https://github.com/sgl-project/sglang.git
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cd sglang
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pip install --upgrade pip
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pip install -e "python[all_hip]"
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```
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## Method 3: Using docker
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## Method 3: Using docker
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The docker images are available on Docker Hub as [lmsysorg/sglang](https://hub.docker.com/r/lmsysorg/sglang/tags), built from [Dockerfile](https://github.com/sgl-project/sglang/tree/main/docker).
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The docker images are available on Docker Hub as [lmsysorg/sglang](https://hub.docker.com/r/lmsysorg/sglang/tags), built from [Dockerfile](https://github.com/sgl-project/sglang/tree/main/docker).
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Replace `<secret>` below with your huggingface hub [token](https://huggingface.co/docs/hub/en/security-tokens).
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Replace `<secret>` below with your huggingface hub [token](https://huggingface.co/docs/hub/en/security-tokens).
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