c32eea96b7
### What this PR does / why we need it?
This PR adds a complete Chinese translation for the documentation using
PO files and the gettext toolchain. The goal is to make the
documentation more accessible to Chinese-speaking users and help the
community grow.
### Does this PR introduce any user-facing change?
Yes. This PR introduces Chinese documentation, which users can access
alongside the original English documentation. No changes to the core
code or APIs.
### How was this patch tested?
The translated documentation was built locally using the standard
documentation build process (`make html` or `sphinx-build`). I checked
the generated HTML pages to ensure the Chinese content displays
correctly and matches the original structure. No code changes were made,
so no additional code tests are required.
vLLM version: v0.9.2
vLLM main: vllm-project/vllm@5780121
---
Please review the translation and let me know if any improvements are
needed. I am happy to update the translation based on feedback.
- vLLM version: v0.9.2
- vLLM main:
7ba34b1241
---------
Signed-off-by: aidoczh <aidoczh@163.com>
Signed-off-by: Yikun Jiang <yikunkero@gmail.com>
Co-authored-by: Yikun Jiang <yikunkero@gmail.com>
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# SOME DESCRIPTIVE TITLE.
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# Copyright (C) 2025, vllm-ascend team
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# This file is distributed under the same license as the vllm-ascend
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# package.
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# FIRST AUTHOR <EMAIL@ADDRESS>, 2025.
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#
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#, fuzzy
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msgid ""
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msgstr ""
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"Project-Id-Version: vllm-ascend\n"
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"Report-Msgid-Bugs-To: \n"
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"POT-Creation-Date: 2025-07-18 09:01+0800\n"
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"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
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"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
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"Language-Team: zh_CN <LL@li.org>\n"
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"Language: zh_CN\n"
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"MIME-Version: 1.0\n"
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"Content-Type: text/plain; charset=utf-8\n"
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"Content-Transfer-Encoding: 8bit\n"
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"Plural-Forms: nplurals=1; plural=0;\n"
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"Generated-By: Babel 2.17.0\n"
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#: ../../faqs.md:1
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msgid "FAQs"
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msgstr ""
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#: ../../faqs.md:3
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msgid "Version Specific FAQs"
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msgstr "特定版本常见问题"
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#: ../../faqs.md:5
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msgid ""
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"[[v0.7.3.post1] FAQ & Feedback](https://github.com/vllm-project/vllm-"
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"ascend/issues/1007)"
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msgstr ""
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"[[v0.7.3.post1] 常见问题与反馈](https://github.com/vllm-project/vllm-"
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"ascend/issues/1007)"
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#: ../../faqs.md:6
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msgid ""
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"[[v0.9.2rc1] FAQ & Feedback](https://github.com/vllm-project/vllm-"
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"ascend/issues/1742)"
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msgstr ""
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"[[v0.9.2rc1] 常见问题与反馈](https://github.com/vllm-project/vllm-"
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"ascend/issues/1742)"
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#: ../../faqs.md:8
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msgid "General FAQs"
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msgstr "常见问题解答"
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#: ../../faqs.md:10
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msgid "1. What devices are currently supported?"
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msgstr "1. 目前支持哪些设备？"
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#: ../../faqs.md:12
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msgid ""
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"Currently, **ONLY** Atlas A2 series(Ascend-cann-kernels-910b) and Atlas "
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"300I(Ascend-cann-kernels-310p) series are supported:"
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msgstr ""
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"目前，**仅**支持 Atlas A2 系列（Ascend-cann-kernels-910b）和 Atlas 300I（Ascend-cann-"
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"kernels-310p）系列："
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#: ../../faqs.md:14
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msgid ""
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"Atlas A2 Training series (Atlas 800T A2, Atlas 900 A2 PoD, Atlas 200T A2 "
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"Box16, Atlas 300T A2)"
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msgstr ""
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"Atlas A2 训练系列（Atlas 800T A2，Atlas 900 A2 PoD，Atlas 200T A2 Box16，Atlas 300T "
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"A2）"
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#: ../../faqs.md:15
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msgid "Atlas 800I A2 Inference series (Atlas 800I A2)"
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msgstr "Atlas 800I A2 推理系列（Atlas 800I A2）"
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#: ../../faqs.md:16
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msgid "Atlas 300I Inference series (Atlas 300I Duo)"
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msgstr "Atlas 300I 推理系列（Atlas 300I Duo）"
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#: ../../faqs.md:18
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msgid "Below series are NOT supported yet:"
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msgstr "以下系列目前尚不受支持："
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#: ../../faqs.md:19
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msgid "Atlas 200I A2 (Ascend-cann-kernels-310b) unplanned yet"
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msgstr "Atlas 200I A2（Ascend-cann-kernels-310b）尚未计划"
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#: ../../faqs.md:20
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msgid "Ascend 910, Ascend 910 Pro B (Ascend-cann-kernels-910) unplanned yet"
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msgstr "Ascend 910，Ascend 910 Pro B（Ascend-cann-kernels-910）尚未计划"
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#: ../../faqs.md:22
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msgid ""
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"From a technical view, vllm-ascend support would be possible if the torch-"
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"npu is supported. Otherwise, we have to implement it by using custom ops. We"
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" are also welcome to join us to improve together."
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msgstr ""
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"从技术角度来看，如果支持 torch-npu，则可以支持 vllm-ascend。否则，我们需要通过自定义算子来实现。我们也欢迎大家一起加入，共同改进。"
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#: ../../faqs.md:24
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msgid "2. How to get our docker containers?"
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msgstr "2. 如何获取我们的 docker 容器？"
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#: ../../faqs.md:26
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msgid ""
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"You can get our containers at `Quay.io`, e.g., [<u>vllm-"
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"ascend</u>](https://quay.io/repository/ascend/vllm-ascend?tab=tags) and "
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"[<u>cann</u>](https://quay.io/repository/ascend/cann?tab=tags)."
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msgstr ""
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"你可以在 `Quay.io` 获取我们的容器，例如，[<u>vllm-"
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"ascend</u>](https://quay.io/repository/ascend/vllm-ascend?tab=tags) 和 "
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"[<u>cann</u>](https://quay.io/repository/ascend/cann?tab=tags)。"
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#: ../../faqs.md:28
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msgid ""
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"If you are in China, you can use `daocloud` to accelerate your downloading:"
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msgstr "如果你在中国，可以使用 `daocloud` 来加速下载："
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#: ../../faqs.md:36
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msgid "3. What models does vllm-ascend supports?"
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msgstr "3. vllm-ascend 支持哪些模型？"
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#: ../../faqs.md:38
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msgid ""
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"Find more details [<u>here</u>](https://vllm-"
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"ascend.readthedocs.io/en/latest/user_guide/support_matrix/supported_models.html)."
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msgstr ""
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"在[<u>此处</u>](https://vllm-"
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"ascend.readthedocs.io/en/latest/user_guide/support_matrix/supported_models.html)查看更多详细信息。"
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#: ../../faqs.md:40
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msgid "4. How to get in touch with our community?"
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msgstr "4. 如何与我们的社区取得联系？"
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#: ../../faqs.md:42
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msgid ""
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"There are many channels that you can communicate with our community "
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"developers / users:"
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msgstr "你可以通过多种渠道与我们的社区开发者/用户进行交流："
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#: ../../faqs.md:44
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msgid ""
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"Submit a GitHub [<u>issue</u>](https://github.com/vllm-project/vllm-"
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"ascend/issues?page=1)."
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msgstr ""
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"提交一个 GitHub [<u>issue</u>](https://github.com/vllm-project/vllm-"
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"ascend/issues?page=1)。"
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#: ../../faqs.md:45
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msgid ""
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"Join our [<u>weekly "
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"meeting</u>](https://docs.google.com/document/d/1hCSzRTMZhIB8vRq1_qOOjx4c9uYUxvdQvDsMV2JcSrw/edit?tab=t.0#heading=h.911qu8j8h35z)"
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" and share your ideas."
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msgstr ""
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"加入我们的[<u>每周会议</u>](https://docs.google.com/document/d/1hCSzRTMZhIB8vRq1_qOOjx4c9uYUxvdQvDsMV2JcSrw/edit?tab=t.0#heading=h.911qu8j8h35z)，并分享你的想法。"
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#: ../../faqs.md:46
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msgid ""
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"Join our [<u>WeChat</u>](https://github.com/vllm-project/vllm-"
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"ascend/issues/227) group and ask your quenstions."
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msgstr ""
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"加入我们的 [<u>微信群</u>](https://github.com/vllm-project/vllm-ascend/issues/227) "
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"并提问你的问题。"
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#: ../../faqs.md:47
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msgid ""
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"Join our ascend channel in [<u>vLLM "
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"forums</u>](https://discuss.vllm.ai/c/hardware-support/vllm-ascend-"
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"support/6) and publish your topics."
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msgstr ""
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"加入我们在 [<u>vLLM 论坛</u>](https://discuss.vllm.ai/c/hardware-support/vllm-"
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"ascend-support/6) 的 ascend 频道并发布你的话题。"
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#: ../../faqs.md:49
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msgid "5. What features does vllm-ascend V1 supports?"
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msgstr "5. vllm-ascend V1 支持哪些功能？"
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#: ../../faqs.md:51
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msgid ""
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"Find more details [<u>here</u>](https://vllm-"
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"ascend.readthedocs.io/en/latest/user_guide/support_matrix/supported_features.html)."
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msgstr ""
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"在[<u>这里</u>](https://vllm-"
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"ascend.readthedocs.io/en/latest/user_guide/support_matrix/supported_features.html)找到更多详细信息。"
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#: ../../faqs.md:53
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msgid ""
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"6. How to solve the problem of \"Failed to infer device type\" or "
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"\"libatb.so: cannot open shared object file\"?"
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msgstr "6. 如何解决“无法推断设备类型”或“libatb.so：无法打开共享对象文件”问题？"
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#: ../../faqs.md:55
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msgid ""
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"Basically, the reason is that the NPU environment is not configured "
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"correctly. You can:"
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msgstr "基本上，原因是 NPU 环境没有正确配置。你可以："
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#: ../../faqs.md:56
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msgid ""
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"try `source /usr/local/Ascend/nnal/atb/set_env.sh` to enable NNAL package."
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msgstr "尝试运行 `source /usr/local/Ascend/nnal/atb/set_env.sh` 以启用 NNAL 包。"
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#: ../../faqs.md:57
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msgid ""
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"try `source /usr/local/Ascend/ascend-toolkit/set_env.sh` to enable CANN "
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"package."
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msgstr "尝试运行 `source /usr/local/Ascend/ascend-toolkit/set_env.sh` 以启用 CANN 包。"
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#: ../../faqs.md:58
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msgid "try `npu-smi info` to check whether the NPU is working."
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msgstr "尝试运行 `npu-smi info` 来检查 NPU 是否正常工作。"
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#: ../../faqs.md:60
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msgid ""
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"If all above steps are not working, you can try the following code with "
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"python to check whether there is any error:"
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msgstr "如果以上所有步骤都无效，你可以尝试使用以下 python 代码来检查是否有错误："
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#: ../../faqs.md:68
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msgid ""
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"If all above steps are not working, feel free to submit a GitHub issue."
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msgstr "如果以上所有步骤都无法解决问题，欢迎提交一个 GitHub issue。"
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#: ../../faqs.md:70
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msgid "7. How does vllm-ascend perform?"
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msgstr "7. vllm-ascend 的性能如何？"
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#: ../../faqs.md:72
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msgid ""
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"Currently, only some models are improved. Such as `Qwen2.5 VL`, `Qwen3`, "
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"`Deepseek V3`. Others are not good enough. From 0.9.0rc2, Qwen and Deepseek"
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" works with graph mode to play a good performance. What's more, you can "
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"install `mindie-turbo` with `vllm-ascend v0.7.3` to speed up the inference "
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"as well."
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msgstr ""
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"目前，只有部分模型得到了改进，比如 `Qwen2.5 VL`、`Qwen3` 和 `Deepseek V3`。其他模型的效果还不够理想。从 "
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"0.9.0rc2 开始，Qwen 和 Deepseek 已经支持图模式，以获得更好的性能。此外，你还可以在 `vllm-ascend v0.7.3` "
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"上安装 `mindie-turbo`，进一步加速推理。"
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#: ../../faqs.md:74
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msgid "8. How vllm-ascend work with vllm?"
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msgstr "8. vllm-ascend 如何与 vllm 协同工作？"
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#: ../../faqs.md:75
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msgid ""
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"vllm-ascend is a plugin for vllm. Basically, the version of vllm-ascend is "
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"the same as the version of vllm. For example, if you use vllm 0.7.3, you "
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"should use vllm-ascend 0.7.3 as well. For main branch, we will make sure "
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"`vllm-ascend` and `vllm` are compatible by each commit."
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msgstr ""
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"vllm-ascend 是 vllm 的一个插件。基本上，vllm-ascend 的版本与 vllm 的版本是相同的。例如，如果你使用 vllm "
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"0.7.3，你也应该使用 vllm-ascend 0.7.3。对于主分支，我们会确保每次提交都让 `vllm-ascend` 和 `vllm` "
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"保持兼容。"
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#: ../../faqs.md:77
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msgid "9. Does vllm-ascend support Prefill Disaggregation feature?"
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msgstr "9. vllm-ascend 支持 Prefill Disaggregation 功能吗？"
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#: ../../faqs.md:79
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msgid ""
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"Currently, only 1P1D is supported on V0 Engine. For V1 Engine or NPND "
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"support, We will make it stable and supported by vllm-ascend in the future."
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msgstr "目前，V0引擎只支持1P1D。对于V1引擎或NPND的支持，我们将在未来使其稳定并由vllm-ascend支持。"
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#: ../../faqs.md:81
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msgid "10. Does vllm-ascend support quantization method?"
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msgstr "10. vllm-ascend 支持量化方法吗？"
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#: ../../faqs.md:83
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msgid ""
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"Currently, w8a8 quantization is already supported by vllm-ascend originally "
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"on v0.8.4rc2 or higher, If you're using vllm 0.7.3 version, w8a8 "
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"quantization is supporeted with the integration of vllm-ascend and mindie-"
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"turbo, please use `pip install vllm-ascend[mindie-turbo]`."
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msgstr ""
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"目前，w8a8 量化已在 v0.8.4rc2 或更高版本的 vllm-ascend 中原生支持。如果你使用的是 vllm 0.7.3 版本，集成了 "
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"vllm-ascend 和 mindie-turbo 后也支持 w8a8 量化，请使用 `pip install vllm-ascend[mindie-"
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"turbo]`。"
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#: ../../faqs.md:85
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msgid "11. How to run w8a8 DeepSeek model?"
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msgstr "11. 如何运行 w8a8 DeepSeek 模型？"
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#: ../../faqs.md:87
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msgid ""
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"Please following the [inferencing tutorail](https://vllm-"
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"ascend.readthedocs.io/en/latest/tutorials/multi_node.html) and replace model"
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" to DeepSeek."
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msgstr ""
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"请按照[inferencing 教程](https://vllm-"
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"ascend.readthedocs.io/en/latest/tutorials/multi_node.html)进行操作，并将模型更换为 "
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"DeepSeek。"
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#: ../../faqs.md:89
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msgid ""
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"12. There is no output in log when loading models using vllm-ascend, How to "
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"solve it?"
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msgstr "12. 使用 vllm-ascend 加载模型时日志没有输出，如何解决？"
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#: ../../faqs.md:91
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msgid ""
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"If you're using vllm 0.7.3 version, this is a known progress bar display "
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"issue in VLLM, which has been resolved in [this PR](https://github.com/vllm-"
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"project/vllm/pull/12428), please cherry-pick it locally by yourself. "
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"Otherwise, please fill up an issue."
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msgstr ""
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"如果你正在使用 vllm 0.7.3 版本，这是 VLLM 已知的进度条显示问题，已在 [此 PR](https://github.com/vllm-"
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"project/vllm/pull/12428) 中解决，请自行在本地进行 cherry-pick。否则，请提交一个 issue。"
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#: ../../faqs.md:93
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msgid "13. How vllm-ascend is tested"
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msgstr "13. 如何测试 vllm-ascend"
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#: ../../faqs.md:95
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msgid ""
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"vllm-ascend is tested by functional test, performance test and accuracy "
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"test."
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msgstr "vllm-ascend 经过功能测试、性能测试和精度测试。"
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#: ../../faqs.md:97
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msgid ""
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"**Functional test**: we added CI, includes portion of vllm's native unit "
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"tests and vllm-ascend's own unit tests，on vllm-ascend's test, we test basic "
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"functionality、popular models availability and [supported "
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"features](https://vllm-"
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"ascend.readthedocs.io/en/latest/user_guide/support_matrix/supported_features.html)"
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" via e2e test"
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msgstr ""
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"**功能测试**：我们添加了CI，包含了vllm原生单元测试的一部分以及vllm-ascend自己的单元测试。在vllm-"
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"ascend的测试中，我们通过e2e测试验证了基本功能、主流模型可用性和[支持的特性](https://vllm-"
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"ascend.readthedocs.io/en/latest/user_guide/support_matrix/supported_features.html)。"
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#: ../../faqs.md:99
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msgid ""
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"**Performance test**: we provide [benchmark](https://github.com/vllm-"
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"project/vllm-ascend/tree/main/benchmarks) tools for end-to-end performance "
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"benchmark which can easily to re-route locally, we'll publish a perf website"
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" to show the performance test results for each pull request"
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msgstr ""
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"**性能测试**：我们提供了用于端到端性能基准测试的[基准测试](https://github.com/vllm-project/vllm-"
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"ascend/tree/main/benchmarks)工具，可以方便地在本地重新运行。我们将发布一个性能网站，用于展示每个拉取请求的性能测试结果。"
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#: ../../faqs.md:101
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msgid ""
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"**Accuracy test**: we're working on adding accuracy test to CI as well."
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msgstr "**准确性测试**：我们也在努力将准确性测试添加到CI中。"
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#: ../../faqs.md:103
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msgid ""
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"Finnall, for each release, we'll publish the performance test and accuracy "
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"test report in the future."
|
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msgstr "最后，未来每个版本发布时，我们都会公开性能测试和准确性测试报告。"
|
||
|
||
#: ../../faqs.md:105
|
||
msgid "14. How to fix the error \"InvalidVersion\" when using vllm-ascend?"
|
||
msgstr "14. 使用 vllm-ascend 时如何解决 “InvalidVersion” 错误？"
|
||
|
||
#: ../../faqs.md:106
|
||
msgid ""
|
||
"It's usually because you 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. Please set the env "
|
||
"variable `VLLM_VERSION` to the version of vLLM package you have installed. "
|
||
"The format of `VLLM_VERSION` should be `X.Y.Z`."
|
||
msgstr ""
|
||
"这通常是因为你安装了开发版或可编辑版本的 vLLM 包。在这种情况下，我们提供了环境变量 `VLLM_VERSION`，以便用户指定要使用的 vLLM "
|
||
"包版本。请将环境变量 `VLLM_VERSION` 设置为你已安装的 vLLM 包的版本。`VLLM_VERSION` 的格式应为 `X.Y.Z`。"
|
||
|
||
#: ../../faqs.md:108
|
||
msgid "15. How to handle Out Of Memory?"
|
||
msgstr "15. 如何处理内存溢出？"
|
||
|
||
#: ../../faqs.md:109
|
||
msgid ""
|
||
"OOM errors typically occur when the model exceeds the memory capacity of a "
|
||
"single NPU. For general guidance, you can refer to [vLLM's OOM "
|
||
"troubleshooting "
|
||
"documentation](https://docs.vllm.ai/en/latest/getting_started/troubleshooting.html#out-"
|
||
"of-memory)."
|
||
msgstr ""
|
||
"当模型超出单个 NPU 的内存容量时，通常会发生 OOM（内存溢出）错误。一般性的指导可以参考 [vLLM 的 OOM "
|
||
"故障排除文档](https://docs.vllm.ai/en/latest/getting_started/troubleshooting.html#out-"
|
||
"of-memory)。"
|
||
|
||
#: ../../faqs.md:111
|
||
msgid ""
|
||
"In scenarios where NPUs have limited HBM (High Bandwidth Memory) capacity, "
|
||
"dynamic memory allocation/deallocation during inference can exacerbate "
|
||
"memory fragmentation, leading to OOM. To address this:"
|
||
msgstr ""
|
||
"在 NPU 的 HBM（高带宽内存）容量有限的场景下，推理过程中动态内存分配和释放会加剧内存碎片，从而导致 OOM（内存溢出）。为了解决这个问题："
|
||
|
||
#: ../../faqs.md:113
|
||
msgid ""
|
||
"**Adjust `--gpu-memory-utilization`**: If unspecified, will use the default "
|
||
"value of `0.9`. You can decrease this param to reserve more memory to reduce"
|
||
" fragmentation risks. See more note in: [vLLM - Inference and Serving - "
|
||
"Engine "
|
||
"Arguments](https://docs.vllm.ai/en/latest/serving/engine_args.html#vllm.engine.arg_utils-"
|
||
"_engine_args_parser-cacheconfig)."
|
||
msgstr ""
|
||
"**调整 `--gpu-memory-utilization`**：如果未指定，将使用默认值 "
|
||
"`0.9`。你可以降低此参数来预留更多内存，从而降低内存碎片风险。参见更多说明：[vLLM - 推理与服务 - "
|
||
"引擎参数](https://docs.vllm.ai/en/latest/serving/engine_args.html#vllm.engine.arg_utils-"
|
||
"_engine_args_parser-cacheconfig)。"
|
||
|
||
#: ../../faqs.md:115
|
||
msgid ""
|
||
"**Configure `PYTORCH_NPU_ALLOC_CONF`**: Set this environment variable to "
|
||
"optimize NPU memory management. For example, you can `export "
|
||
"PYTORCH_NPU_ALLOC_CONF=expandable_segments:True` to enable virtual memory "
|
||
"feature to mitigate memory fragmentation caused by frequent dynamic memory "
|
||
"size adjustments during runtime, see more note in: "
|
||
"[PYTORCH_NPU_ALLOC_CONF](https://www.hiascend.com/document/detail/zh/Pytorch/700/comref/Envvariables/Envir_012.html)."
|
||
msgstr ""
|
||
"**配置 `PYTORCH_NPU_ALLOC_CONF`**：设置此环境变量以优化NPU内存管理。例如，你可以通过 `export "
|
||
"PYTORCH_NPU_ALLOC_CONF=expandable_segments:True` "
|
||
"来启用虚拟内存功能，以缓解运行时频繁动态调整内存大小导致的内存碎片问题，更多说明参见：[PYTORCH_NPU_ALLOC_CONF](https://www.hiascend.com/document/detail/zh/Pytorch/700/comref/Envvariables/Envir_012.html)。"
|
||
|
||
#: ../../faqs.md:117
|
||
msgid "16. Failed to enable NPU graph mode when running DeepSeek?"
|
||
msgstr "16. 运行 DeepSeek 时无法启用 NPU 图模式？"
|
||
|
||
#: ../../faqs.md:118
|
||
#, python-brace-format
|
||
msgid ""
|
||
"You may encounter the following error if running DeepSeek with NPU graph "
|
||
"mode enabled. The allowed number of queries per kv when enabling both MLA "
|
||
"and Graph mode only support {32, 64, 128}, **Thus this is not supported for "
|
||
"DeepSeek-V2-Lite**, as it only has 16 attention heads. The NPU graph mode "
|
||
"support on DeepSeek-V2-Lite will be done in the future."
|
||
msgstr ""
|
||
"如果在启用NPU图模式（Graph "
|
||
"mode）运行DeepSeek时，您可能会遇到以下错误。当同时启用MLA和图模式时，每个kv允许的查询数只支持{32, 64, "
|
||
"128}，**因此这不支持DeepSeek-V2-Lite**，因为它只有16个注意力头。未来会增加对DeepSeek-V2-Lite在NPU图模式下的支持。"
|
||
|
||
#: ../../faqs.md:120
|
||
#, python-brace-format
|
||
msgid ""
|
||
"And if you're using DeepSeek-V3 or DeepSeek-R1, please make sure after the "
|
||
"tensor parallel split, num_heads / num_kv_heads in {32, 64, 128}."
|
||
msgstr ""
|
||
"如果你正在使用 DeepSeek-V3 或 DeepSeek-R1，请确保在张量并行切分后，num_heads / num_kv_heads 的值为 "
|
||
"{32, 64, 128} 中的一个。"
|
||
|
||
#: ../../faqs.md:127
|
||
msgid ""
|
||
"17. Failed to reinstall vllm-ascend from source after uninstalling vllm-"
|
||
"ascend?"
|
||
msgstr "17. 卸载 vllm-ascend 后无法从源码重新安装 vllm-ascend？"
|
||
|
||
#: ../../faqs.md:128
|
||
msgid ""
|
||
"You may encounter the problem of C compilation failure when reinstalling "
|
||
"vllm-ascend from source using pip. If the installation fails, it is "
|
||
"recommended to use `python setup.py install` to install, or use `python "
|
||
"setup.py clean` to clear the cache."
|
||
msgstr ""
|
||
"当你使用 pip 从源码重新安装 vllm-ascend 时，可能会遇到 C 编译失败的问题。如果安装失败，建议使用 `python setup.py "
|
||
"install` 进行安装，或者使用 `python setup.py clean` 清除缓存。"
|
||
|
||
#: ../../faqs.md:130
|
||
msgid "18. How to generate determinitic results when using vllm-ascend?"
|
||
msgstr "18. 使用 vllm-ascend 时如何生成确定性结果？"
|
||
|
||
#: ../../faqs.md:131
|
||
msgid "There are several factors that affect output certainty:"
|
||
msgstr "有几个因素会影响输出的确定性："
|
||
|
||
#: ../../faqs.md:133
|
||
msgid ""
|
||
"Sampler Method: using **Greedy sample** by setting `temperature=0` in "
|
||
"`SamplingParams`, e.g.:"
|
||
msgstr ""
|
||
"采样方法：通过在 `SamplingParams` 中设置 `temperature=0` 来使用 **贪婪采样（Greedy "
|
||
"sample）**，例如："
|
||
|
||
#: ../../faqs.md:158
|
||
msgid "Set the following enveriments parameters:"
|
||
msgstr "设置以下环境参数："
|