# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, vllm-kunlun team # This file is distributed under the same license as the vllm-kunlun # package. # FIRST AUTHOR , 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 \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 A2,Atlas 900" #~ " A2 PoD,Atlas 200T A2 Box16,Atlas " #~ "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。"