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<p>You are viewing the latest developer preview docs. <ahref="https://vllm-ascend.readthedocs.io/en/stable/">Click here</a> to view docs for the latest stable release(v0.7.3).</p>
Copy file name to clipboardExpand all lines: docs/source/developer_guide/versioning_policy.md
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@@ -74,7 +74,7 @@ Usually, each minor version of vLLM (such as 0.7) will correspond to a vLLM Asce
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For main branch, vLLM Ascend should works with vLLM main branch and latest 1 or 2 release version. So to ensure the backward compatibility, we will do the following:
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- Both main branch and target vLLM release is tested by Ascend E2E CI. For example, currently, vLLM main branch and vLLM 0.8.4 are tested now.
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- For code changes, we will make sure that the changes are compatible with the latest 1 or 2 vLLM release version as well. In this case, vLLM Ascend introduced a version check machinism inner the code. It'll check the version of installed vLLM pacakge first to decide which code logic to use. If users hit the `InvalidVersion` error, it sometimes means that they have installed an dev/editable version of vLLM package. In this case, we provide the env variable `VLLM_VERSION` to let users specify the version of vLLM package to use.
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- For code changes, we will make sure that the changes are compatible with the latest 1 or 2 vLLM release version as well. In this case, vLLM Ascend introduced a version check machinism inner the code. It'll check the version of installed vLLM package first to decide which code logic to use. If users hit the `InvalidVersion` error, it sometimes means that they have installed an dev/editable version of vLLM package. In this case, we provide the env variable `VLLM_VERSION` to let users specify the version of vLLM package to use.
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- For documentation changes, we will make sure that the changes are compatible with the latest 1 or 2 vLLM release version as well. Note should be added if there are any breaking changes.
Copy file name to clipboardExpand all lines: docs/source/faqs.md
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### 10. Does vllm-ascend support quantization method?
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Currently, w8a8 quantization is already supported by vllm-ascend originally on v0.8.4rc2 or heigher, If you're using vllm 0.7.3 version, w8a8 quantization is supporeted with the integration of vllm-ascend and mindie-turbo, please use `pip install vllm-ascend[mindie-turbo]`.
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Currently, w8a8 quantization is already supported by vllm-ascend originally on v0.8.4rc2 or higher, If you're using vllm 0.7.3 version, w8a8 quantization is supporeted with the integration of vllm-ascend and mindie-turbo, please use `pip install vllm-ascend[mindie-turbo]`.
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- DeepSeek V3/R1 works with DP, TP and MTP now. Please note that it's still in experimental status. Let us know if you hit any problem. [#429](https://github.com/vllm-project/vllm-ascend/pull/429)[#585](https://github.com/vllm-project/vllm-ascend/pull/585)[#626](https://github.com/vllm-project/vllm-ascend/pull/626)[#636](https://github.com/vllm-project/vllm-ascend/pull/636)[#671](https://github.com/vllm-project/vllm-ascend/pull/671)
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### Core
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- ACLGraph feature is supported with V1 engine now. It's disabled by default because this feature rely on CANN 8.1 release. We'll make it avaiable by default in the next release [#426](https://github.com/vllm-project/vllm-ascend/pull/426)
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- Upgrade PyTorch to 2.5.1. vLLM Ascend no longer relies on the dev version of torch-npu now. Now users don't need to install the torch-npu by hand. The 2.5.1 version of torch-npu will be installed automaticlly. [#661](https://github.com/vllm-project/vllm-ascend/pull/661)
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- ACLGraph feature is supported with V1 engine now. It's disabled by default because this feature rely on CANN 8.1 release. We'll make it available by default in the next release [#426](https://github.com/vllm-project/vllm-ascend/pull/426)
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- Upgrade PyTorch to 2.5.1. vLLM Ascend no longer relies on the dev version of torch-npu now. Now users don't need to install the torch-npu by hand. The 2.5.1 version of torch-npu will be installed automatically. [#661](https://github.com/vllm-project/vllm-ascend/pull/661)
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### Other
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- MiniCPM model works now. [#645](https://github.com/vllm-project/vllm-ascend/pull/645)
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