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# SOME DESCRIPTIVE TITLE.
# Copyright (C) 2025, vllm-kunlun team
# This file is distributed under the same license as the vllm-kunlun
# package.
# FIRST AUTHOR <EMAIL@ADDRESS>, 2025.
#
#, fuzzy
msgid ""
msgstr ""
"Project-Id-Version: vllm-kunlun\n"
"Report-Msgid-Bugs-To: \n"
"POT-Creation-Date: 2025-11-10 16:59+0800\n"
"PO-Revision-Date: 2025-07-18 10:09+0800\n"
"Last-Translator: \n"
"Language: zh_CN\n"
"Language-Team: zh_CN <LL@li.org>\n"
"Plural-Forms: nplurals=1; plural=0;\n"
"MIME-Version: 1.0\n"
"Content-Type: text/plain; charset=utf-8\n"
"Content-Transfer-Encoding: 8bit\n"
"Generated-By: Babel 2.17.0\n"
#: ../../source/quick_start.md:1
msgid "Quickstart"
msgstr "快速入门"
#: ../../source/quick_start.md:3
msgid "Prerequisites"
msgstr "先决条件"
#: ../../source/quick_start.md:5
msgid "Supported Devices"
msgstr "支持的设备"
#~ msgid ""
#~ "Atlas A2 Training series (Atlas 800T "
#~ "A2, Atlas 900 A2 PoD, Atlas 200T"
#~ " A2 Box16, Atlas 300T A2)"
#~ msgstr ""
#~ "Atlas A2 训练系列Atlas 800T A2Atlas 900"
#~ " A2 PoDAtlas 200T A2 Box16Atlas "
#~ "300T A2"
#~ msgid "Atlas 800I A2 Inference series (Atlas 800I A2)"
#~ msgstr "Atlas 800I A2 推理系列Atlas 800I A2"
#~ msgid "Setup environment using container"
#~ msgstr "使用容器设置环境"
#~ msgid "Ubuntu"
#~ msgstr "Ubuntu"
#~ msgid "openEuler"
#~ msgstr "openEuler"
#~ msgid ""
#~ "The default workdir is `/workspace`, "
#~ "vLLM and vLLM Kunlun code are "
#~ "placed in `/vllm-workspace` and "
#~ "installed in [development "
#~ "mode](https://setuptools.pypa.io/en/latest/userguide/development_mode.html)(`pip"
#~ " install -e`) to help developer "
#~ "immediately take place changes without "
#~ "requiring a new installation."
#~ msgstr ""
#~ "默认的工作目录是 `/workspace`vLLM 和 vLLM Kunlun "
#~ "代码被放置在 `/vllm-"
#~ "workspace`,并以[开发模式](https://setuptools.pypa.io/en/latest/userguide/development_mode.html)`pip"
#~ " install -e`)安装,以便开发者能够即时生效更改,而无需重新安装。"
#~ msgid "Usage"
#~ msgstr "用法"
#~ msgid "You can use Modelscope mirror to speed up download:"
#~ msgstr "你可以使用 Modelscope 镜像来加速下载:"
#~ msgid "There are two ways to start vLLM on Kunlun XPU:"
#~ msgstr "在昇腾 XPU 上启动 vLLM 有两种方式:"
#~ msgid "Offline Batched Inference"
#~ msgstr "离线批量推理"
#~ msgid ""
#~ "With vLLM installed, you can start "
#~ "generating texts for list of input "
#~ "prompts (i.e. offline batch inferencing)."
#~ 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)。"
#~ msgid ""
#~ "Try to run below Python script "
#~ "directly or use `python3` shell to "
#~ "generate texts:"
#~ 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:"
#~ msgid "OpenAI Completions API"
#~ msgstr "OpenAI Completions API"
#~ msgid ""
#~ "vLLM can also be deployed as a "
#~ "server that implements the OpenAI API"
#~ " protocol. Run the following command "
#~ "to start the vLLM server with the"
#~ " [Qwen/Qwen2.5-0.5B-"
#~ "Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) "
#~ "model:"
#~ msgstr ""
#~ "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"
#~ " [Qwen/Qwen2.5-0.5B-"
#~ "Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) "
#~ "模型启动 vLLM 服务器:"
#~ msgid "If you see log as below:"
#~ msgstr "如果你看到如下日志:"
#~ msgid "Congratulations, you have successfully started the vLLM server!"
#~ msgstr "恭喜,你已经成功启动了 vLLM 服务器!"
#~ msgid "You can query the list the models:"
#~ msgstr "你可以查询模型列表:"
#~ msgid "You can also query the model with input prompts:"
#~ msgstr "你也可以通过输入提示来查询模型:"
#~ msgid ""
#~ "vLLM is serving as background process,"
#~ " you can use `kill -2 $VLLM_PID` "
#~ "to stop the background process "
#~ "gracefully, it's equal to `Ctrl-C` to"
#~ " stop foreground vLLM process:"
#~ msgstr ""
#~ "vLLM 正作为后台进程运行,你可以使用 `kill -2 $VLLM_PID` "
#~ "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:"
#~ msgid "You will see output as below:"
#~ msgstr "你将会看到如下输出:"
#~ msgid "Finally, you can exit container by using `ctrl-D`."
#~ msgstr "最后,你可以通过按 `ctrl-D` 退出容器。"