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vermouth1992 merged 1 commit into from
May 24, 2025
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modify the installation method of vllm on different architectures and hyperlink #1673

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5 changes: 4 additions & 1 deletion docs/ascend/ascend_vllm073.rst
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Expand Up @@ -55,7 +55,10 @@ vLLM
git clone -b v0.7.3 --depth 1 https://github.com/vllm-project/vllm.git
cd vllm
pip install -r requirements-build.txt
# for Atlas 200T A2 Box16
VLLM_TARGET_DEVICE=empty pip install -e . --extra-index https://download.pytorch.org/whl/cpu/
# for Atlas 800T A2
VLLM_TARGET_DEVICE=empty pip install -e .

.. code-block:: bash

Expand Down Expand Up @@ -83,7 +86,7 @@ vLLM
.. image:: https://github.com/eric-haibin-lin/verl-community/blob/main/docs/loss_comparison.png?raw=true
:alt: loss_comparison

其中，N 表示训练的步数。更多信息请参考[精度计算说明](https://www.hiascend.com/document/detail/zh/Pytorch/600/ptmoddevg/trainingmigrguide/LMaccuracy_0001.html)。
其中，N 表示训练的步数。更多信息请参考 `精度计算说明 <https://www.hiascend.com/document/detail/zh/Pytorch/600/ptmoddevg/trainingmigrguide/LMaccuracy_0001.html>`_。

根据经验，对于GRPO等强化学习算法，我们期望在相同配置下，在华为昇腾设备上的 reward 与英伟达 GPU 的 reward 平均绝对误差小于等于 4%，具体计算参考 Loss 计算。

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