[Doc] Update README and docs for v0.28.0 (#6858)
Signed-off-by: hsliuustc0106 <liuhongsheng4@huawei.com>
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@@ -34,7 +34,7 @@ vLLM-Omni is a Python library that supports the following GPU variants. The libr
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### Pre-built wheels
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Note: Pre-built wheels are currently available for vLLM-Omni 0.11.0rc1, 0.12.0rc1, 0.14.0rc1, 0.14.0, 0.16.0, 0.18.0, 0.20.0, 0.21.0, 0.22.0, 0.23.0, 0.24.0, 0.25.0, and 0.26.0; the 0.28.0 wheels are published together with the v0.28.0 release this branch produces. If you need a newer unreleased revision, please [build from source](https://docs.vllm.ai/projects/vllm-omni/en/latest/getting_started/installation/gpu/#build-wheel-from-source).
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Note: Pre-built wheels are currently available for vLLM-Omni 0.11.0rc1, 0.12.0rc1, 0.14.0rc1, 0.14.0, 0.16.0, 0.18.0, 0.20.0, 0.21.0, 0.22.0, 0.23.0, 0.24.0, 0.25.0, 0.26.0, and 0.28.0. If you need a newer unreleased revision, please [build from source](https://docs.vllm.ai/projects/vllm-omni/en/latest/getting_started/installation/gpu/#build-wheel-from-source).
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=== "NVIDIA CUDA"
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@@ -5,7 +5,7 @@
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# --8<-- [end:requirements]
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# --8<-- [start:set-up-using-python]
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vLLM-Omni depends on the matching major/minor release of vLLM. The vLLM-Omni 0.26.x release line uses vLLM 0.26.x.
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vLLM-Omni depends on the matching major/minor release of vLLM. The vLLM-Omni 0.28.x release line uses vLLM 0.28.x.
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!!! note
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PyTorch installed via `conda` will statically link `NCCL` library, which can cause issues when vLLM tries to use `NCCL`. See <gh-issue:8420> for more details.
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@@ -95,6 +95,13 @@ uv pip install --no-build-isolation --editable .
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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](https://hub.docker.com/r/vllm/vllm-omni/tags). The version of vLLM-Omni indicates which release of vLLM it is based on.
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Nightly CUDA images built from the latest `main` are also available:
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- [`vllm/vllm-omni:nightly`](https://hub.docker.com/r/vllm/vllm-omni/tags?name=nightly) is the rolling multi-architecture tag.
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- [`vllm/vllm-omni:nightly-<commit>`](https://hub.docker.com/r/vllm/vllm-omni/tags?name=nightly-) provides commit-pinned multi-architecture tags. The newest 14 are retained.
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Use a commit-pinned tag when you need a reproducible nightly environment.
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Here's an example deployment command that has been verified on 2 x H100's:
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```bash
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docker run --runtime nvidia --gpus 2 \
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@@ -9,8 +9,8 @@ The recommended way to use vLLM-Omni on NPU is through the vLLM-Ascend pre-built
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```bash
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# vLLM-Ascend image
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# Atlas A2: quay.io/atlas-ci/vllm-ascend:v0.26.0
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# Atlas A3: quay.io/atlas-ci/vllm-ascend:v0.26.0-a3
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# Atlas A2: quay.io/atlas-ci/vllm-ascend:v0.28.0
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# Atlas A3: quay.io/atlas-ci/vllm-ascend:v0.28.0-a3
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docker run --rm \
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--name vllm-omni-npu \
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--shm-size=1g \
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@@ -28,11 +28,11 @@ docker run --rm \
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-v /etc/ascend_install.info:/etc/ascend_install.info \
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-v /root/.cache:/root/.cache \
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-p 8000:8000 \
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-it quay.io/atlas-ci/vllm-ascend:v0.26.0-a3 bash
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-it quay.io/atlas-ci/vllm-ascend:v0.28.0-a3 bash
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# Inside the container, install vLLM-Omni from source
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cd /vllm-workspace
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git clone -b v0.26.0 https://github.com/vllm-project/vllm-omni.git
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git clone -b v0.28.0 https://github.com/vllm-project/vllm-omni.git
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cd vllm-omni
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pip install -v -e . --no-build-isolation
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# or VLLM_OMNI_TARGET_DEVICE=npu pip install -v -e .
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@@ -50,21 +50,11 @@ We are keeping [issue #886](https://github.com/vllm-project/vllm-omni/issues/886
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# --8<-- [start:installation-main]
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You can also build vLLM-Omni from the latest main branch if you want to use the latest features or bug fixes. (But sometimes it will break for a while. You can check [issue #886](https://github.com/vllm-project/vllm-omni/issues/886) for the status of the latest commit of vLLM-Omni main branch on NPU.)
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You can also install vLLM-Omni from the latest main branch if you want to use the latest features or bug fixes. Use the aligned vLLM-Ascend v0.28.0 image described above, and check [issue #886](https://github.com/vllm-project/vllm-omni/issues/886) for the status of the latest vLLM-Omni commit on NPU.
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```bash
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# Pin vLLM and vLLM-Ascend to the v0.26 release line
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git clone -b v0.26.0 https://github.com/vllm-project/vllm.git
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cd vllm
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VLLM_TARGET_DEVICE=empty pip install -v -e .
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cd ..
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git clone -b releases/v0.26.0rc https://github.com/vllm-project/vllm-ascend.git
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cd vllm-ascend
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pip install -v -e .
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cd ..
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# Install vLLM-Omni from the latest main branch
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# Inside the vLLM-Ascend v0.28.0 container, install vLLM-Omni from main
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cd /vllm-workspace
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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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pip install -v -e . --no-build-isolation
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@@ -88,8 +78,8 @@ Supported images as following.
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Here's an example deployment command that has been verified on 4 x NPUs:
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```bash
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# Atlas A2: quay.io/ascend/vllm-omni:v0.26.0
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# Atlas A3: quay.io/ascend/vllm-omni:v0.26.0-a3
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# Atlas A2: quay.io/ascend/vllm-omni:v0.28.0
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# Atlas A3: quay.io/ascend/vllm-omni:v0.28.0-a3
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docker run --rm \
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--name vllm-omni-a3 \
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--shm-size=4g \
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@@ -114,7 +104,7 @@ docker run --rm \
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-v /etc/ascend_install.info:/etc/ascend_install.info \
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-v ~/.cache:/root/.cache \
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-p 8091:8091 \
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-it quay.io/ascend/vllm-omni:v0.26.0-a3 bash
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-it quay.io/ascend/vllm-omni:v0.28.0-a3 bash
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```
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!!! tip
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