140 lines
4.5 KiB
Plaintext
140 lines
4.5 KiB
Plaintext
# SOME DESCRIPTIVE TITLE.
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# Copyright (C) 2025, vllm-kunlun team
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# This file is distributed under the same license as the vllm-kunlun
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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-kunlun\n"
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"Report-Msgid-Bugs-To: \n"
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"POT-Creation-Date: 2025-11-10 16:59+0800\n"
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"PO-Revision-Date: 2025-07-18 10:09+0800\n"
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"Last-Translator: \n"
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"Language: zh_CN\n"
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"Language-Team: zh_CN <LL@li.org>\n"
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"Plural-Forms: nplurals=1; plural=0;\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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"Generated-By: Babel 2.17.0\n"
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#: ../../source/quick_start.md:1
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msgid "Quickstart"
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msgstr "快速入门"
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#: ../../source/quick_start.md:3
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msgid "Prerequisites"
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msgstr "先决条件"
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#: ../../source/quick_start.md:5
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msgid "Supported Devices"
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msgstr "支持的设备"
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#~ msgid ""
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#~ "Atlas A2 Training series (Atlas 800T "
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#~ "A2, Atlas 900 A2 PoD, Atlas 200T"
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#~ " A2 Box16, Atlas 300T A2)"
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#~ msgstr ""
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#~ "Atlas A2 训练系列（Atlas 800T A2，Atlas 900"
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#~ " A2 PoD，Atlas 200T A2 Box16，Atlas "
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#~ "300T A2）"
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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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#~ msgid "Setup environment using container"
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#~ msgstr "使用容器设置环境"
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#~ msgid "Ubuntu"
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#~ msgstr "Ubuntu"
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#~ msgid "openEuler"
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#~ msgstr "openEuler"
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#~ msgid ""
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#~ "The default workdir is `/workspace`, "
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#~ "vLLM and vLLM Kunlun code are "
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#~ "placed in `/vllm-workspace` and "
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#~ "installed in [development "
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#~ "mode](https://setuptools.pypa.io/en/latest/userguide/development_mode.html)(`pip"
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#~ " install -e`) to help developer "
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#~ "immediately take place changes without "
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#~ "requiring a new installation."
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#~ msgstr ""
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#~ "默认的工作目录是 `/workspace`，vLLM 和 vLLM Kunlun "
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#~ "代码被放置在 `/vllm-"
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#~ "workspace`，并以[开发模式](https://setuptools.pypa.io/en/latest/userguide/development_mode.html)（`pip"
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#~ " install -e`）安装，以便开发者能够即时生效更改，而无需重新安装。"
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#~ msgid "Usage"
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#~ msgstr "用法"
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#~ msgid "You can use Modelscope mirror to speed up download:"
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#~ msgstr "你可以使用 Modelscope 镜像来加速下载："
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#~ msgid "There are two ways to start vLLM on Kunlun XPU:"
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#~ msgstr "在昇腾 XPU 上启动 vLLM 有两种方式："
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#~ msgid "Offline Batched Inference"
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#~ msgstr "离线批量推理"
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#~ msgid ""
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#~ "With vLLM installed, you can start "
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#~ "generating texts for list of input "
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#~ "prompts (i.e. offline batch inferencing)."
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#~ msgstr "安装了 vLLM 后，您可以开始为一系列输入提示生成文本（即离线批量推理）。"
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#~ msgid ""
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#~ "Try to run below Python script "
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#~ "directly or use `python3` shell to "
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#~ "generate texts:"
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#~ msgstr "尝试直接运行下面的 Python 脚本，或者使用 `python3` 交互式命令行来生成文本："
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#~ msgid "OpenAI Completions API"
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#~ msgstr "OpenAI Completions API"
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#~ msgid ""
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#~ "vLLM can also be deployed as a "
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#~ "server that implements the OpenAI API"
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#~ " protocol. Run the following command "
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#~ "to start the vLLM server with the"
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#~ " [Qwen/Qwen2.5-0.5B-"
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#~ "Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) "
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#~ "model:"
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#~ msgstr ""
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#~ "vLLM 也可以作为实现 OpenAI API 协议的服务器进行部署。运行以下命令，使用"
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#~ " [Qwen/Qwen2.5-0.5B-"
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#~ "Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) "
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#~ "模型启动 vLLM 服务器："
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#~ msgid "If you see log as below:"
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#~ msgstr "如果你看到如下日志："
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#~ msgid "Congratulations, you have successfully started the vLLM server!"
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#~ msgstr "恭喜，你已经成功启动了 vLLM 服务器！"
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#~ msgid "You can query the list the models:"
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#~ msgstr "你可以查询模型列表："
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#~ msgid "You can also query the model with input prompts:"
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#~ msgstr "你也可以通过输入提示来查询模型："
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#~ msgid ""
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#~ "vLLM is serving as background process,"
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#~ " you can use `kill -2 $VLLM_PID` "
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#~ "to stop the background process "
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#~ "gracefully, it's equal to `Ctrl-C` to"
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#~ " stop foreground vLLM process:"
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#~ msgstr ""
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#~ "vLLM 正作为后台进程运行，你可以使用 `kill -2 $VLLM_PID` "
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#~ "来优雅地停止后台进程，这等同于使用 `Ctrl-C` 停止前台 vLLM 进程："
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#~ msgid "You will see output as below:"
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#~ msgstr "你将会看到如下输出："
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#~ msgid "Finally, you can exit container by using `ctrl-D`."
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#~ msgstr "最后，你可以通过按 `ctrl-D` 退出容器。"
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