提交vllm0.11.0开发分支

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chenyili
2025-12-10 17:51:24 +08:00
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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: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\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/user_guide/configuration/additional_config.md:1
msgid "Additional Configuration"
msgstr "附加配置"
#~ msgid ""
#~ "additional configuration is a mechanism "
#~ "provided by vLLM to allow plugins "
#~ "to control inner behavior by their "
#~ "own. vLLM Kunlun uses this mechanism "
#~ "to make the project more flexible."
#~ msgstr "额外配置是 vLLM 提供的一种机制允许插件自行控制内部行为。vLLM Kunlun 利用这种机制使项目更加灵活。"
#~ msgid "How to use"
#~ msgstr "如何使用"
#~ msgid ""
#~ "With either online mode or offline "
#~ "mode, users can use additional "
#~ "configuration. Take Qwen3 as an example:"
#~ msgstr "无论是在线模式还是离线模式,用户都可以使用额外的配置。以 Qwen3 为例:"
#~ msgid "**Online mode**:"
#~ msgstr "**在线模式**"
#~ msgid "**Offline mode**:"
#~ msgstr "**离线模式**"
#~ msgid "Configuration options"
#~ msgstr "配置选项"
#~ msgid ""
#~ "The following table lists the additional"
#~ " configuration options available in vLLM"
#~ " Kunlun:"
#~ msgstr "下表列出了 vLLM Kunlun 中可用的其他配置选项:"
#~ msgid "Name"
#~ msgstr "名称"
#~ msgid "Type"
#~ msgstr "类型"
#~ msgid "Default"
#~ msgstr "默认"
#~ msgid "Description"
#~ msgstr "描述"
#~ msgid "`torchair_graph_config`"
#~ msgstr "`torchair_graph_config`"
#~ msgid "dict"
#~ msgstr "dict"
#~ msgid "`{}`"
#~ msgstr "`{}`"
#~ msgid "The config options for torchair graph mode"
#~ msgstr "torchair 图模式的配置选项"
#~ msgid "`kunlun_scheduler_config`"
#~ msgstr "`kunlun_scheduler_config`"
#~ msgid "The config options for kunlun scheduler"
#~ msgstr "kunlun 调度器的配置选项"
#~ msgid "`expert_tensor_parallel_size`"
#~ msgstr "`expert_tensor_parallel_size`"
#~ msgid "str"
#~ msgstr "str"
#~ msgid "`0`"
#~ msgstr "`0`"
#~ msgid "Expert tensor parallel size the model to use."
#~ msgstr "专家张量并行的模型大小设置。"
#~ msgid "`refresh`"
#~ msgstr "`刷新`"
#~ msgid "bool"
#~ msgstr "bool"
#~ msgid "`false`"
#~ msgstr "`false`"
#~ msgid ""
#~ "Whether to refresh global kunlun config"
#~ " content. This value is usually used"
#~ " by rlhf or ut/e2e test case."
#~ msgstr "是否刷新全局 kunlun 配置信息。此值通常由 rlhf 或 ut/e2e 测试用例使用。"
#~ msgid "`expert_map_path`"
#~ msgstr "`expert_map_path`"
#~ msgid "`None`"
#~ msgstr "`None`"
#~ msgid ""
#~ "When using expert load balancing for "
#~ "the MOE model, an expert map path"
#~ " needs to be passed in."
#~ msgstr "在为MOE模型使用专家负载均衡时需要传入专家映射路径。"
#~ msgid "`False`"
#~ msgstr "`False`"
#~ msgid "Whether to enable the fused operator-like chunked_prefill."
#~ msgstr "是否启用类似算子融合的 chunked_prefill 功能。"
#~ msgid "`kv_cache_dtype`"
#~ msgstr "`kv_cache_dtype`"
#~ msgid ""
#~ "When using the kv cache quantization "
#~ "method, kv cache dtype needs to be"
#~ " set, currently only int8 is "
#~ "supported."
#~ msgstr "当使用kv缓存量化方法时需要设置kv缓存的数据类型目前仅支持int8。"
#~ msgid "The details of each config option are as follows:"
#~ msgstr "每个配置选项的详细信息如下:"
#~ msgid "**torchair_graph_config**"
#~ msgstr "**torchair_graph_config**"
#~ msgid "`enabled`"
#~ msgstr "`启用`"
#~ msgid ""
#~ "Whether to enable torchair graph mode."
#~ " Currently only DeepSeek series models "
#~ "and PanguProMoE are supported to use "
#~ "torchair graph mode"
#~ msgstr "是否启用 torchair 图模式。目前仅支持 DeepSeek 系列模型和 PanguProMoE 使用 torchair 图模式。"
#~ msgid "`enable_multistream_mla`"
#~ msgstr "`enable_multistream_mla`"
#~ msgid ""
#~ "Whether to put vector ops of MLA"
#~ " to another stream. This option only"
#~ " takes effects on models using MLA"
#~ " (e.g., DeepSeek)."
#~ msgstr "是否将MLA的向量操作放到另一个流中。此选项仅对使用MLA的模型例如DeepSeek有效。"
#~ msgid "`multistream_overlap_shared_expert`"
#~ msgstr "`multistream_overlap_shared_expert`"
#~ msgid ""
#~ "Whether to enable multistream shared "
#~ "expert. This option only takes effects"
#~ " on DeepSeek moe models."
#~ msgstr "是否启用多流共享专家功能。此选项仅对 DeepSeek MoE 模型生效。"
#~ msgid "`enable_view_optimize`"
#~ msgstr "`enable_view_optimize` (启用视图优化)"
#~ msgid "`True`"
#~ msgstr "`True`"
#~ msgid "Whether to enable torchair view optimization"
#~ msgstr "是否启用torchair视图优化"
#~ msgid "`use_cached_graph`"
#~ msgstr "`use_cached_graph`"
#~ msgid "Whether to use cached graph"
#~ msgstr "是否使用缓存的图"
#~ msgid "`graph_batch_sizes`"
#~ msgstr "`graph_batch_sizes`"
#~ msgid "list[int]"
#~ msgstr "list[int]"
#~ msgid "`[]`"
#~ msgstr "`[]`"
#~ msgid "The batch size for torchair graph cache"
#~ msgstr "torchair 图缓存的批量大小"
#~ msgid "`graph_batch_sizes_init`"
#~ msgstr "`graph_batch_sizes_init`"
#~ msgid "Init graph batch size dynamically if `graph_batch_sizes` is empty"
#~ msgstr "如果 `graph_batch_sizes` 为空,则动态初始化图批大小"
#~ msgid "`enable_kv_nz`"
#~ msgstr "`enable_kv_nz`"
#~ msgid ""
#~ "Whether to enable kvcache NZ layout. "
#~ "This option only takes effects on "
#~ "models using MLA (e.g., DeepSeek)."
#~ msgstr "是否启用 kvcache NZ 布局。此选项仅对使用 MLA 的模型(例如 DeepSeek生效。"
#~ msgid "**kunlun_scheduler_config**"
#~ msgstr "**kunlun_scheduler_config**"
#~ msgid "Whether to enable kunlun scheduler for V1 engine"
#~ msgstr "是否为 V1 引擎启用 kunlun 调度器"
#~ msgid ""
#~ "kunlun_scheduler_config also support the "
#~ "options from [vllm scheduler "
#~ "config](https://docs.vllm.ai/en/stable/api/vllm/config.html#vllm.config.SchedulerConfig)."
#~ " For example, you can add "
#~ "`enable_chunked_prefill: True` to "
#~ "kunlun_scheduler_config as well."
#~ msgstr ""
#~ "kunlun_scheduler_config 也支持来自 [vllm scheduler "
#~ "config](https://docs.vllm.ai/en/stable/api/vllm/config.html#vllm.config.SchedulerConfig)"
#~ " 的选项。例如,你也可以在 kunlun_scheduler_config 中添加 "
#~ "`enable_chunked_prefill: True`。"
#~ msgid "Example"
#~ msgstr "示例"
#~ msgid "An example of additional configuration is as follows:"
#~ msgstr "以下是额外配置的一个示例:"

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# Translations template for PROJECT.
# Copyright (C) 2025 ORGANIZATION
# This file is distributed under the same license as the PROJECT project.
# FIRST AUTHOR <EMAIL@ADDRESS>, 2025.
#
#, fuzzy
msgid ""
msgstr ""
"Project-Id-Version: PROJECT VERSION\n"
"Report-Msgid-Bugs-To: EMAIL@ADDRESS\n"
"POT-Creation-Date: 2025-11-10 16:59+0800\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
"Language-Team: LANGUAGE <LL@li.org>\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/user_guide/configuration/env_vars.md:1
msgid "Environment Variables"
msgstr "环境变量"
#~ msgid ""
#~ "vllm-kunlun uses the following "
#~ "environment variables to configure the "
#~ "system:"
#~ msgstr "vllm-kunlun 使用以下环境变量来配置系统:"

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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 19:12+0800\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\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/user_guide/configuration/index.md:1
#: ../../source/user_guide/configuration/index.md:5
msgid "Configuration Guide"
msgstr "配置指南"
#: ../../source/user_guide/configuration/index.md:3
#, fuzzy
msgid "This section provides a detailed configuration guide of vLLM Kunlun."
msgstr "本节提供了 vLLM Kunlun 的详细配置指南。"

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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: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\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/user_guide/feature_guide/dynamic_batch.md:1
msgid "Dynamic Batch"
msgstr ""

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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: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\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/user_guide/feature_guide/eplb_swift_balancer.md:1
msgid "Expert Load Balance (EPLB)"
msgstr ""
#: ../../source/user_guide/feature_guide/eplb_swift_balancer.md:3
msgid "Overview"
msgstr ""

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# Translations template for PROJECT.
# Copyright (C) 2025 ORGANIZATION
# This file is distributed under the same license as the PROJECT project.
# FIRST AUTHOR <EMAIL@ADDRESS>, 2025.
#
#, fuzzy
msgid ""
msgstr ""
"Project-Id-Version: PROJECT VERSION\n"
"Report-Msgid-Bugs-To: EMAIL@ADDRESS\n"
"POT-Creation-Date: 2025-11-10 16:59+0800\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
"Language-Team: LANGUAGE <LL@li.org>\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/user_guide/feature_guide/graph_mode.md:1
msgid "Graph Mode Guide"
msgstr "图模式指南"
#~ msgid ""
#~ "This feature is currently experimental. "
#~ "In future versions, there may be "
#~ "behavioral changes around configuration, "
#~ "coverage, performance improvement."
#~ msgstr "此功能目前为实验性功能。在未来的版本中,配置、覆盖率和性能改进等方面的行为可能会有变化。"
#~ msgid ""
#~ "This guide provides instructions for "
#~ "using Kunlun Graph Mode with vLLM "
#~ "Kunlun. Please note that graph mode "
#~ "is only available on V1 Engine. "
#~ "And only Qwen, DeepSeek series models"
#~ " are well tested from 0.9.0rc1. We'll"
#~ " make it stable and generalize in "
#~ "the next release."
#~ msgstr ""
#~ "本指南提供了在 vLLM Kunlun 上使用 Kunlun "
#~ "图模式的操作说明。请注意,图模式仅在 V1 引擎上可用,并且从 0.9.0rc1 起,仅对"
#~ " Qwen、DeepSeek 系列模型进行了充分测试。我们将在下一个版本中使其更加稳定和通用。"
#~ msgid "Getting Started"
#~ msgstr "快速入门"
#~ msgid ""
#~ "From v0.9.1rc1 with V1 Engine, vLLM "
#~ "Kunlun will run models in graph "
#~ "mode by default to keep the same"
#~ " behavior with vLLM. If you hit "
#~ "any issues, please feel free to "
#~ "open an issue on GitHub and "
#~ "fallback to eager mode temporarily by"
#~ " set `enforce_eager=True` when initializing "
#~ "the model."
#~ msgstr ""
#~ "从 v0.9.1rc1 版本起,使用 V1 引擎时vLLM Kunlun"
#~ " 默认将在图模式下运行模型,以保持与 vLLM 同样的行为。如果遇到任何问题,欢迎在 GitHub"
#~ " 上提交 issue并在初始化模型时通过设置 `enforce_eager=True` "
#~ "临时切换回 eager 模式。"
#~ msgid "There are two kinds for graph mode supported by vLLM Kunlun:"
#~ msgstr "vLLM Kunlun 支持两种图模式:"
#~ msgid ""
#~ "**ACLGraph**: This is the default graph"
#~ " mode supported by vLLM Kunlun. In"
#~ " v0.9.1rc1, only Qwen series models "
#~ "are well tested."
#~ msgstr ""
#~ "**ACLGraph**:这是 vLLM Kunlun 支持的默认图模式。在 "
#~ "v0.9.1rc1 版本中,只有 Qwen 系列模型得到了充分测试。"
#~ msgid ""
#~ "**TorchAirGraph**: This is the GE graph"
#~ " mode. In v0.9.1rc1, only DeepSeek "
#~ "series models are supported."
#~ msgstr "**TorchAirGraph**这是GE图模式。在v0.9.1rc1版本中仅支持DeepSeek系列模型。"
#~ msgid "Using ACLGraph"
#~ msgstr "使用 ACLGraph"
#~ msgid ""
#~ "ACLGraph is enabled by default. Take "
#~ "Qwen series models as an example, "
#~ "just set to use V1 Engine is "
#~ "enough."
#~ msgstr "ACLGraph 默认启用。以 Qwen 系列模型为例,只需设置为使用 V1 引擎即可。"
#~ msgid "offline example:"
#~ msgstr "离线示例:"
#~ msgid "online example:"
#~ msgstr "在线示例:"
#~ msgid "Using TorchAirGraph"
#~ msgstr "使用 TorchAirGraph"
#~ msgid ""
#~ "If you want to run DeepSeek series"
#~ " models with graph mode, you should"
#~ " use "
#~ "[TorchAirGraph](https://www.hikunlun.com/document/detail/zh/Pytorch/700/modthirdparty/torchairuseguide/torchair_0002.html)."
#~ " In this case, additional config is"
#~ " required."
#~ msgstr ""
#~ "如果你想通过图模式运行 DeepSeek 系列模型,你应该使用 "
#~ "[TorchAirGraph](https://www.hikunlun.com/document/detail/zh/Pytorch/700/modthirdparty/torchairuseguide/torchair_0002.html)。在这种情况下,需要额外的配置。"
#~ msgid ""
#~ "You can find more detail about "
#~ "additional config "
#~ "[here](../configuration/additional_config.md)."
#~ msgstr "你可以在[这里](../configuration/additional_config.md)找到关于附加配置的更多详细信息。"
#~ msgid "Fallback to Eager Mode"
#~ msgstr "回退到 Eager 模式"
#~ msgid ""
#~ "If both `ACLGraph` and `TorchAirGraph` "
#~ "fail to run, you should fallback "
#~ "to eager mode."
#~ msgstr "如果 `ACLGraph` 和 `TorchAirGraph` 都无法运行,你应该退回到 eager 模式。"

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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 19:12+0800\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\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/user_guide/feature_guide/index.md:1
#: ../../source/user_guide/feature_guide/index.md:5
msgid "Feature Guide"
msgstr "功能指南"
#: ../../source/user_guide/feature_guide/index.md:3
#, fuzzy
msgid "This section provides a detailed usage guide of vLLM Kunlun features."
msgstr "本节提供了 vLLM Kunlun 功能的详细使用指南。"

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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: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\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/user_guide/feature_guide/kv_pool_mooncake.md:1
msgid "Mooncacke Store Deployment Guide"
msgstr ""
#: ../../source/user_guide/feature_guide/kv_pool_mooncake.md:3
msgid "Environmental Dependencies"
msgstr ""

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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: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\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/user_guide/feature_guide/lora.md:1
msgid "LoRA Adapters Guide"
msgstr "LoRA 适配器指南"
#: ../../source/user_guide/feature_guide/lora.md:3
msgid "Overview"
msgstr ""
#~ msgid ""
#~ "Like vLLM, vllm-kunlun supports LoRA "
#~ "as well. The usage and more "
#~ "details can be found in [vLLM "
#~ "official "
#~ "document](https://docs.vllm.ai/en/latest/features/lora.html)."
#~ msgstr ""
#~ "与 vLLM 类似vllm-kunlun 也支持 "
#~ "LoRA。用法及更多详情可参见 [vLLM "
#~ "官方文档](https://docs.vllm.ai/en/latest/features/lora.html)。"
#~ msgid ""
#~ "You can also refer to "
#~ "[this](https://docs.vllm.ai/en/latest/models/supported_models.html"
#~ "#list-of-text-only-language-models) "
#~ "to find which models support LoRA "
#~ "in vLLM."
#~ msgstr ""
#~ "你也可以参考[这个链接](https://docs.vllm.ai/en/latest/models/supported_models.html"
#~ "#list-of-text-only-language-models)来查找哪些模型在"
#~ " vLLM 中支持 LoRA。"
#~ msgid "Tips"
#~ msgstr "提示"
#~ msgid ""
#~ "If you fail to run vllm-kunlun "
#~ "with LoRA, you may follow [this "
#~ "instruction](https://vllm-"
#~ "kunlun.readthedocs.io/en/latest/user_guide/feature_guide/graph_mode.html"
#~ "#fallback-to-eager-mode) to disable "
#~ "graph mode and try again."
#~ msgstr ""
#~ "如果你在使用 LoRA 运行 vllm-kunlun "
#~ "时失败,可以按照[此说明](https://vllm-"
#~ "kunlun.readthedocs.io/en/latest/user_guide/feature_guide/graph_mode.html"
#~ "#fallback-to-eager-mode)禁用图模式后再重试。"

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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: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\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/user_guide/feature_guide/netloader.md:1
msgid "Netloader Guide"
msgstr ""

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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: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\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/user_guide/feature_guide/quantization.md:1
msgid "Quantization Guide"
msgstr "量化指南"
#~ msgid ""
#~ "Model quantization is a technique that"
#~ " reduces the size and computational "
#~ "requirements of a model by lowering "
#~ "the data precision of the weights "
#~ "and activation values in the model, "
#~ "thereby saving the memory and improving"
#~ " the inference speed."
#~ msgstr "模型量化是一种通过降低模型中权重和激活值的数据精度,从而减少模型大小和计算需求的技术,这样可以节省内存并提高推理速度。"
#~ msgid ""
#~ "Since 0.9.0rc2 version, quantization feature"
#~ " is experimentally supported in vLLM "
#~ "Kunlun. Users can enable quantization "
#~ "feature by specifying `--quantization kunlun`."
#~ " Currently, only Qwen, DeepSeek series "
#~ "models are well tested. Well support"
#~ " more quantization algorithm and models "
#~ "in the future."
#~ msgstr ""
#~ "自 0.9.0rc2 版本起vLLM Kunlun 实验性地支持量化特性。用户可以通过指定"
#~ " `--quantization kunlun` 启用量化功能。目前,只有 "
#~ "Qwen、DeepSeek 系列模型经过了充分测试。未来我们将支持更多的量化算法和模型。"
#~ msgid "Install modelslim"
#~ msgstr "安装 modelslim"
#~ msgid ""
#~ "To quantize a model, users should "
#~ "install "
#~ "[ModelSlim](https://gitcode.com/Kunlun/msit/blob/master/msmodelslim/README.md)"
#~ " which is the Kunlun compression and"
#~ " acceleration tool. It is an "
#~ "affinity-based compression tool designed "
#~ "for acceleration, using compression as "
#~ "its core technology and built upon "
#~ "the Kunlun platform."
#~ msgstr "要对模型进行量化,用户应安装[ModelSlim](https://gitcode.com/Kunlun/msit/blob/master/msmodelslim/README.md),这是昇腾的压缩与加速工具。它是一种基于亲和性的压缩工具,专为加速设计,以压缩为核心技术,并基于昇腾平台构建。"
#~ msgid ""
#~ "Currently, only the specific tag "
#~ "[modelslim-"
#~ "VLLM-8.1.RC1.b020_001](https://gitcode.com/Kunlun/msit/blob"
#~ "/modelslim-VLLM-8.1.RC1.b020_001/msmodelslim/README.md) of"
#~ " modelslim works with vLLM Kunlun. "
#~ "Please do not install other version "
#~ "until modelslim master version is "
#~ "available for vLLM Kunlun in the "
#~ "future."
#~ msgstr ""
#~ "目前,只有 modelslim 的特定标签 [modelslim-"
#~ "VLLM-8.1.RC1.b020_001](https://gitcode.com/Kunlun/msit/blob"
#~ "/modelslim-VLLM-8.1.RC1.b020_001/msmodelslim/README.md) 支持"
#~ " vLLM Kunlun。在未来 modelslim 的主版本支持 vLLM "
#~ "Kunlun 之前,请不要安装其他版本。"
#~ msgid "Install modelslim:"
#~ msgstr "安装 modelslim"
#~ msgid "Quantize model"
#~ msgstr "量化模型"
#~ msgid ""
#~ "Take [DeepSeek-V2-Lite](https://modelscope.cn/models"
#~ "/deepseek-ai/DeepSeek-V2-Lite) as an example, "
#~ "you just need to download the "
#~ "model, and then execute the convert "
#~ "command. The command is shown below. "
#~ "More info can be found in "
#~ "modelslim doc [deepseek w8a8 dynamic "
#~ "quantization docs](https://gitcode.com/Kunlun/msit/blob"
#~ "/modelslim-"
#~ "VLLM-8.1.RC1.b020_001/msmodelslim/example/DeepSeek/README.md#deepseek-v2-w8a8-dynamic%E9%87%8F%E5%8C%96)."
#~ msgstr ""
#~ "以 [DeepSeek-V2-Lite](https://modelscope.cn/models/deepseek-"
#~ "ai/DeepSeek-V2-Lite) 为例,你只需要下载模型,然后执行转换命令。命令如下所示。更多信息可参考 "
#~ "modelslim 文档 [deepseek w8a8 "
#~ "动态量化文档](https://gitcode.com/Kunlun/msit/blob/modelslim-"
#~ "VLLM-8.1.RC1.b020_001/msmodelslim/example/DeepSeek/README.md#deepseek-v2-w8a8-dynamic%E9%87%8F%E5%8C%96)。"
#~ msgid ""
#~ "You can also download the quantized "
#~ "model that we uploaded. Please note "
#~ "that these weights should be used "
#~ "for test only. For example, "
#~ "https://www.modelscope.cn/models/vllm-kunlun/DeepSeek-V2"
#~ "-Lite-W8A8"
#~ msgstr ""
#~ "你也可以下载我们上传的量化模型。请注意这些权重仅应用于测试。例如https://www.modelscope.cn/models"
#~ "/vllm-kunlun/DeepSeek-V2-Lite-W8A8"
#~ msgid "Once convert action is done, there are two important files generated."
#~ msgstr "转换操作完成后,会生成两个重要的文件。"
#~ msgid ""
#~ "[config.json](https://www.modelscope.cn/models/vllm-"
#~ "kunlun/DeepSeek-V2-Lite-"
#~ "W8A8/file/view/master/config.json?status=1). Please make"
#~ " sure that there is no "
#~ "`quantization_config` field in it."
#~ msgstr ""
#~ "[config.json](https://www.modelscope.cn/models/vllm-"
#~ "kunlun/DeepSeek-V2-Lite-"
#~ "W8A8/file/view/master/config.json?status=1)。请确保其中没有 "
#~ "`quantization_config` 字段。"
#~ msgid ""
#~ "[quant_model_description.json](https://www.modelscope.cn/models"
#~ "/vllm-kunlun/DeepSeek-V2-Lite-"
#~ "W8A8/file/view/master/quant_model_description.json?status=1). "
#~ "All the converted weights info are "
#~ "recorded in this file."
#~ msgstr ""
#~ "[quant_model_description.json](https://www.modelscope.cn/models"
#~ "/vllm-kunlun/DeepSeek-V2-Lite-"
#~ "W8A8/file/view/master/quant_model_description.json?status=1)。所有被转换的权重信息都记录在该文件中。"
#~ msgid "Here is the full converted model files:"
#~ msgstr "以下是完整转换后的模型文件:"
#~ msgid "Run the model"
#~ msgstr "运行模型"
#~ msgid ""
#~ "Now, you can run the quantized "
#~ "models with vLLM Kunlun. Here is "
#~ "the example for online and offline "
#~ "inference."
#~ msgstr "现在,你可以使用 vLLM Kunlun 运行量化模型。下面是在线和离线推理的示例。"
#~ msgid "Offline inference"
#~ msgstr "离线推理"
#~ msgid "Online inference"
#~ msgstr "在线推理"
#~ msgid "FAQs"
#~ msgstr "常见问题解答"
#~ msgid ""
#~ "1. How to solve the KeyError: "
#~ "'xxx.layers.0.self_attn.q_proj.weight' problem?"
#~ msgstr "1. 如何解决 KeyError: 'xxx.layers.0.self_attn.q_proj.weight' 问题?"
#~ msgid ""
#~ "First, make sure you specify `kunlun`"
#~ " quantization method. Second, check if "
#~ "your model is converted by this "
#~ "`modelslim-VLLM-8.1.RC1.b020_001` modelslim version."
#~ " Finally, if it still doesn't work,"
#~ " please submit a issue, maybe some"
#~ " new models need to be adapted."
#~ msgstr ""
#~ "首先,请确保你指定了 `kunlun` 量化方法。其次,检查你的模型是否由 `modelslim-"
#~ "VLLM-8.1.RC1.b020_001` 这个 modelslim "
#~ "版本转换。如果仍然无法使用,请提交一个 issue可能有一些新模型需要适配。"
#~ msgid ""
#~ "2. How to solve the error \"Could"
#~ " not locate the configuration_deepseek.py\"?"
#~ msgstr "2. 如何解决“无法找到 configuration_deepseek.py”错误"
#~ msgid ""
#~ "Please convert DeepSeek series models "
#~ "using `modelslim-VLLM-8.1.RC1.b020_001` modelslim,"
#~ " this version has fixed the missing"
#~ " configuration_deepseek.py error."
#~ msgstr ""
#~ "请使用 `modelslim-VLLM-8.1.RC1.b020_001` 的 "
#~ "modelslim 转换 DeepSeek 系列模型,该版本已修复缺少 "
#~ "configuration_deepseek.py 的错误。"

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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: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\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/user_guide/feature_guide/sleep_mode.md:1
msgid "Sleep Mode Guide"
msgstr "睡眠模式指南"
#: ../../source/user_guide/feature_guide/sleep_mode.md:3
msgid "Overview"
msgstr "概述"
#~ msgid ""
#~ "Sleep Mode is an API designed to"
#~ " offload model weights and discard KV"
#~ " cache from XPU memory. This "
#~ "functionality is essential for reinforcement"
#~ " learning (RL) post-training workloads, "
#~ "particularly in online algorithms such "
#~ "as PPO, GRPO, or DPO. During "
#~ "training, the policy model typically "
#~ "performs auto-regressive generation using "
#~ "inference engines like vLLM, followed by"
#~ " forward and backward passes for "
#~ "optimization."
#~ msgstr ""
#~ "Sleep Mode 是一个用于卸载模型权重并清除 XPU 内存中 KV "
#~ "缓存的 API。此功能对于强化学习RL后训练任务尤其重要特别是在 PPO、GRPO 或 "
#~ "DPO 等在线算法中。在训练过程中,策略模型通常会使用像 vLLM "
#~ "这样的推理引擎进行自回归生成,然后进行前向和反向传播以进行优化。"
#~ msgid ""
#~ "Since the generation and training phases"
#~ " may employ different model parallelism "
#~ "strategies, it becomes crucial to free"
#~ " KV cache and even offload model "
#~ "parameters stored within vLLM during "
#~ "training. This ensures efficient memory "
#~ "utilization and avoids resource contention "
#~ "on the XPU."
#~ msgstr ""
#~ "由于生成和训练阶段可能采用不同的模型并行策略,因此在训练过程中及时释放 KV 缓存,甚至卸载存储在 "
#~ "vLLM 内的模型参数变得至关重要。这可以确保内存的高效利用,并避免 XPU 上的资源争用。"
#~ msgid "Getting started"
#~ msgstr "快速上手"
#~ msgid ""
#~ "With `enable_sleep_mode=True`, the way we "
#~ "manage memory(malloc, free) in vllm will"
#~ " under a specific memory pool, during"
#~ " loading model and initialize kv_caches,"
#~ " we tag the memory as a map:"
#~ " `{\"weight\": data, \"kv_cache\": data}`."
#~ msgstr ""
#~ "当 `enable_sleep_mode=True` 时,我们在 vllm "
#~ "中管理内存malloc, free的方式会在一个特定的内存池下进行在加载模型和初始化 kv_caches"
#~ " 期间,我们会将内存打上标签,组织成一个映射:`{\"weight\": data, "
#~ "\"kv_cache\": data}`。"
#~ msgid ""
#~ "The engine(v0/v1) supports two sleep "
#~ "levels to manage memory during idle "
#~ "periods:"
#~ msgstr "该引擎v0/v1支持两种睡眠等级以在空闲期间管理内存"
#~ msgid "Level 1 Sleep"
#~ msgstr "一级睡眠"
#~ msgid "Action: Offloads model weights and discards the KV cache."
#~ msgstr "操作卸载模型权重并清除KV缓存。"
#~ msgid "Memory: Model weights are moved to CPU memory; KV cache is forgotten."
#~ msgstr "内存模型权重被移动到CPU内存KV缓存被清除。"
#~ msgid "Use Case: Suitable when reusing the same model later."
#~ msgstr "用例:适用于之后需要重复使用同一个模型的情况。"
#~ msgid ""
#~ "Note: Ensure sufficient CPU memory is"
#~ " available to hold the model weights."
#~ msgstr "注意请确保有足够的CPU内存来存储模型权重。"
#~ msgid "Level 2 Sleep"
#~ msgstr "二级睡眠"
#~ msgid "Action: Discards both model weights and KV cache."
#~ msgstr "操作同时丢弃模型权重和KV缓存。"
#~ msgid ""
#~ "Memory: The content of both the "
#~ "model weights and kv cache is "
#~ "forgotten."
#~ msgstr "内存模型权重和kv缓存的内容都会被遗忘。"
#~ msgid ""
#~ "Use Case: Ideal when switching to "
#~ "a different model or updating the "
#~ "current one."
#~ msgstr "用例:当切换到不同的模型或更新当前模型时非常理想。"
#~ msgid ""
#~ "Since this feature uses the low-"
#~ "level API "
#~ "[KunlunCL](https://www.hikunlun.com/document/detail/zh/CANNCommunityEdition/82RC1alpha002/API/appdevgapi/appdevgapi_07_0000.html),"
#~ " in order to use sleep mode, "
#~ "you should follow the [installation "
#~ "guide](https://vllm-"
#~ "kunlun.readthedocs.io/en/latest/installation.html) and "
#~ "building from source, if you are "
#~ "using v0.7.3, remember to set `export"
#~ " COMPILE_CUSTOM_KERNELS=1`, for the latest "
#~ "version(v0.9.x+), the environment variable "
#~ "`COMPILE_CUSTOM_KERNELS` will be set 1 "
#~ "by default while building from source."
#~ msgstr ""
#~ "由于此功能使用了底层 API "
#~ "[KunlunCL](https://www.hikunlun.com/document/detail/zh/CANNCommunityEdition/82RC1alpha002/API/appdevgapi/appdevgapi_07_0000.html),为了使用休眠模式,你应按照[安装指南](https"
#~ "://vllm-"
#~ "kunlun.readthedocs.io/en/latest/installation.html)进行操作,并从源码编译。如果你使用的是"
#~ " v0.7.3,请记得设置 `export COMPILE_CUSTOM_KERNELS=1` "
#~ "对于最新版本v0.9.x+),在从源码编译时环境变量 `COMPILE_CUSTOM_KERNELS` "
#~ "默认会被设置为 1。"
#~ msgid "Usage"
#~ msgstr "用法"
#~ msgid "The following is a simple example of how to use sleep mode."
#~ msgstr "以下是如何使用睡眠模式的一个简单示例。"
#~ msgid "offline inference:"
#~ msgstr "离线推理:"
#~ msgid "online serving:"
#~ msgstr "在线服务:"
#~ msgid ""
#~ "Considering there may be a risk of"
#~ " malicious access, please make sure "
#~ "you are under a dev-mode, and "
#~ "explicit specify the develop env: "
#~ "`VLLM_SERVER_DEV_MODE` to expose these "
#~ "endpoints(sleep/wake up)."
#~ msgstr ""
#~ "鉴于可能存在恶意访问的风险,请确保您处于开发模式,并明确指定开发环境:`VLLM_SERVER_DEV_MODE`以便开放这些端点sleep/wake"
#~ " up。"

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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: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\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/user_guide/feature_guide/structured_output.md:1
msgid "Structured Output Guide"
msgstr "结构化输出指南"
#: ../../source/user_guide/feature_guide/structured_output.md:3
msgid "Overview"
msgstr "概述"
#: ../../source/user_guide/feature_guide/structured_output.md:5
#, fuzzy
msgid "What is structured output?"
msgstr "什么是结构化输出?"
#~ msgid ""
#~ "LLMs can be unpredictable when you "
#~ "need output in specific formats. Think"
#~ " of asking a model to generate "
#~ "JSON - without guidance, it might "
#~ "produce valid text that breaks JSON "
#~ "specification. **Structured Output (also "
#~ "called Guided Decoding)** enables LLMs "
#~ "to generate outputs that follow a "
#~ "desired structure while preserving the "
#~ "non-deterministic nature of the system."
#~ msgstr ""
#~ "当你需要特定格式输出时大型语言模型LLMs可能表现出不可预测性。比如让模型生成 "
#~ "JSON如果没有指导模型可能会生成有效的文本但这些文本却不符合 JSON "
#~ "规范。**结构化输出(也称为引导解码)** 能让大型语言模型生成符合预期结构的输出,同时保留系统的非确定性特性。"
#~ msgid ""
#~ "In simple terms, structured decoding "
#~ "gives LLMs a “template” to follow. "
#~ "Users provide a schema that “influences”"
#~ " the models output, ensuring compliance"
#~ " with the desired structure."
#~ msgstr "简单来说结构化解码为LLM提供了一个“模板”来遵循。用户提供一个模式来“影响”模型的输出从而确保输出符合期望的结构。"
#~ msgid "![structured decoding](./images/structured_output_1.png)"
#~ msgstr "![结构化解码](./images/structured_output_1.png)"
#~ msgid "structured decoding"
#~ msgstr "结构化解码"
#~ msgid "Structured Output in vllm-kunlun"
#~ msgstr "vllm-kunlun 中的结构化输出"
#~ msgid ""
#~ "Currently, vllm-kunlun supports **xgrammar**"
#~ " and **guidance** backend for structured"
#~ " output with vllm v1 engine."
#~ msgstr "目前vllm-kunlun 支持 vllm v1 引擎的结构化输出,后端包括 **xgrammar** 和 **guidance**。"
#~ msgid ""
#~ "XGrammar introduces a new technique that"
#~ " batch constrained decoding via pushdown"
#~ " automaton (PDA). You can think of"
#~ " a PDA as a “collection of "
#~ "FSMs, and each FSM represents a "
#~ "context-free grammar (CFG).” One "
#~ "significant advantage of PDA is its "
#~ "recursive nature, allowing us to execute"
#~ " multiple state transitions. They also "
#~ "include additional optimisation (for those "
#~ "who are interested) to reduce grammar"
#~ " compilation overhead. Besides, you can "
#~ "also find more details about guidance"
#~ " by yourself."
#~ msgstr ""
#~ "XGrammar 引入了一种通过下推自动机PDA进行批量约束解码的新技术。你可以把 PDA "
#~ "理解为“有限状态机FSM的集合每个 FSM 代表一个上下文无关文法CFG。” PDA "
#~ "的一个重要优点是其递归特性使我们能够执行多次状态转移。此外PDA "
#~ "还包含了额外的优化(供感兴趣的用户参考),以减少语法编译的开销。除此之外,你还可以自己找到更多关于指导的信息。"
#~ msgid "How to Use Structured Output?"
#~ msgstr "如何使用结构化输出?"
#~ msgid "Online Inference"
#~ msgstr "在线推理"
#~ msgid ""
#~ "You can also generate structured outputs"
#~ " using the OpenAI's Completions and "
#~ "Chat API. The following parameters are"
#~ " supported, which must be added as"
#~ " extra parameters:"
#~ msgstr "你也可以使用 OpenAI 的 Completions 和 Chat API 生成结构化输出。支持以下参数,这些参数必须作为额外参数添加:"
#~ msgid "`guided_choice`: the output will be exactly one of the choices."
#~ msgstr "`guided_choice`:输出将会是其中一个选项。"
#~ msgid "`guided_regex`: the output will follow the regex pattern."
#~ msgstr "`guided_regex`:输出将遵循正则表达式模式。"
#~ msgid "`guided_json`: the output will follow the JSON schema."
#~ msgstr "`guided_json`:输出将遵循 JSON 架构。"
#~ msgid "`guided_grammar`: the output will follow the context free grammar."
#~ msgstr "`guided_grammar`:输出将遵循上下文无关文法。"
#~ msgid ""
#~ "Structured outputs are supported by "
#~ "default in the OpenAI-Compatible Server."
#~ " You can choose to specify the "
#~ "backend to use by setting the "
#~ "`--guided-decoding-backend` flag to vllm"
#~ " serve. The default backend is "
#~ "`auto`, which will try to choose "
#~ "an appropriate backend based on the "
#~ "details of the request. You may "
#~ "also choose a specific backend, along"
#~ " with some options."
#~ msgstr ""
#~ "OpenAI 兼容服务器默认支持结构化输出。你可以通过设置 `--guided-decoding-"
#~ "backend` 标志为 vllm serve 来指定要使用的后端。默认后端为 "
#~ "`auto`,它会根据请求的详细信息尝试选择合适的后端。你也可以选择特定的后端,并设置一些选项。"
#~ msgid ""
#~ "Now let´s see an example for each"
#~ " of the cases, starting with the "
#~ "guided_choice, as it´s the easiest one:"
#~ msgstr "现在让我们来看每种情况的示例,首先是 guided_choice因为它是最简单的"
#~ msgid ""
#~ "The next example shows how to use"
#~ " the guided_regex. The idea is to "
#~ "generate an email address, given a "
#~ "simple regex template:"
#~ msgstr "下一个例子展示了如何使用 guided_regex。其思路是基于一个简单的正则表达式模板生成一个电子邮件地址"
#~ msgid ""
#~ "One of the most relevant features "
#~ "in structured text generation is the "
#~ "option to generate a valid JSON "
#~ "with pre-defined fields and formats. "
#~ "For this we can use the "
#~ "guided_json parameter in two different "
#~ "ways:"
#~ msgstr ""
#~ "在结构化文本生成中,最相关的特性之一是能够生成具有预定义字段和格式的有效 JSON。为此我们可以通过两种不同的方式使用 "
#~ "guided_json 参数:"
#~ msgid "Using a JSON Schema."
#~ msgstr "使用 JSON 架构。"
#~ msgid "Defining a Pydantic model and then extracting the JSON Schema from it."
#~ msgstr "定义一个 Pydantic 模型,然后从中提取 JSON Schema。"
#~ msgid ""
#~ "The next example shows how to use"
#~ " the guided_json parameter with a "
#~ "Pydantic model:"
#~ msgstr "下一个示例展示了如何将 guided_json 参数与 Pydantic 模型一起使用:"
#~ msgid ""
#~ "Finally we have the guided_grammar "
#~ "option, which is probably the most "
#~ "difficult to use, but it´s really "
#~ "powerful. It allows us to define "
#~ "complete languages like SQL queries. It"
#~ " works by using a context free "
#~ "EBNF grammar. As an example, we "
#~ "can use to define a specific "
#~ "format of simplified SQL queries:"
#~ msgstr ""
#~ "最后,我们有 guided_grammar 选项,这可能是最难使用的,但它非常强大。它允许我们定义完整的语言,比如"
#~ " SQL 查询。它通过使用上下文无关的 EBNF 语法来实现。例如,我们可以用它来定义一种简化"
#~ " SQL 查询的特定格式:"
#~ msgid ""
#~ "Find more examples [here](https://github.com"
#~ "/vllm-"
#~ "project/vllm/blob/main/examples/offline_inference/structured_outputs.py)."
#~ msgstr ""
#~ "在[这里](https://github.com/vllm-"
#~ "project/vllm/blob/main/examples/offline_inference/structured_outputs.py)可以找到更多示例。"
#~ msgid "Offline Inference"
#~ msgstr "离线推理"
#~ msgid ""
#~ "To use Structured Output, we'll need "
#~ "to configure the guided decoding using"
#~ " the class `GuidedDecodingParams` inside "
#~ "`SamplingParams`. The main available options"
#~ " inside `GuidedDecodingParams` are:"
#~ msgstr ""
#~ "要使用结构化输出,我们需要在 `SamplingParams` 内通过 "
#~ "`GuidedDecodingParams` 类配置引导解码。`GuidedDecodingParams` "
#~ "中主要可用的选项有:"
#~ msgid "json"
#~ msgstr "json"
#~ msgid "regex"
#~ msgstr "正则表达式"
#~ msgid "choice"
#~ msgstr "选择"
#~ msgid "grammar"
#~ msgstr "语法"
#~ msgid "One example for the usage of the choice parameter is shown below:"
#~ msgstr "choice 参数用法的一个示例如下:"
#~ msgid ""
#~ "Find more examples of other usages "
#~ "[here](https://github.com/vllm-"
#~ "project/vllm/blob/main/examples/offline_inference/structured_outputs.py)."
#~ msgstr ""
#~ "查看更多其他用法的示例 [在这里](https://github.com/vllm-"
#~ "project/vllm/blob/main/examples/offline_inference/structured_outputs.py)。"

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# Translations template for PROJECT.
# Copyright (C) 2025 ORGANIZATION
# This file is distributed under the same license as the PROJECT project.
# FIRST AUTHOR <EMAIL@ADDRESS>, 2025.
#
#, fuzzy
msgid ""
msgstr ""
"Project-Id-Version: PROJECT VERSION\n"
"Report-Msgid-Bugs-To: EMAIL@ADDRESS\n"
"POT-Creation-Date: 2025-11-10 16:59+0800\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
"Language-Team: LANGUAGE <LL@li.org>\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/user_guide/support_matrix/index.md:5
msgid "Support Matrix"
msgstr "支持矩阵"
#: ../../source/user_guide/support_matrix/index.md:1
#, fuzzy
msgid "Features and Models"
msgstr "特性与模型"
#: ../../source/user_guide/support_matrix/index.md:3
#, fuzzy
msgid "This section provides a detailed matrix supported by vLLM Kunlun."
msgstr "本节提供了 vLLM Kunlun 的详细支持矩阵。"

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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: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\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/user_guide/support_matrix/supported_features.md:1
msgid "Supported Features"
msgstr ""
#: ../../source/user_guide/support_matrix/supported_features.md:3
msgid "The feature support principle of vLLM"
msgstr ""
#~ msgid "Feature Support"
#~ msgstr "功能支持"
#~ msgid ""
#~ "The feature support principle of vLLM"
#~ " Kunlun is: **aligned with the "
#~ "vLLM**. We are also actively "
#~ "collaborating with the community to "
#~ "accelerate support."
#~ msgstr "vLLM Kunlun 的特性支持原则是:**与 vLLM 保持一致**。我们也在积极与社区合作,加快支持进度。"
#~ msgid ""
#~ "You can check the [support status "
#~ "of vLLM V1 Engine][v1_user_guide]. Below "
#~ "is the feature support status of "
#~ "vLLM Kunlun:"
#~ msgstr "你可以查看 [vLLM V1 引擎的支持状态][v1_user_guide]。下面是 vLLM Kunlun 的功能支持情况:"
#~ msgid "Feature"
#~ msgstr "特性"
#~ msgid "vLLM V0 Engine"
#~ msgstr "vLLM V0 引擎"
#~ msgid "vLLM V1 Engine"
#~ msgstr "vLLM V1 引擎"
#~ msgid "Next Step"
#~ msgstr "下一步"
#~ msgid "Chunked Prefill"
#~ msgstr "分块预填充"
#~ msgid "🟢 Functional"
#~ msgstr "🟢 功能性"
#~ msgid "Functional, see detail note: [Chunked Prefill][cp]"
#~ msgstr "功能性,详见说明:[分块预填充][cp]"
#~ msgid "Automatic Prefix Caching"
#~ msgstr "自动前缀缓存"
#~ msgid "Functional, see detail note: [vllm-kunlun#732][apc]"
#~ msgstr "可用,请参见详细说明:[vllm-kunlun#732][apc]"
#~ msgid "LoRA"
#~ msgstr "LoRA"
#~ msgid "[vllm-kunlun#396][multilora], [vllm-kunlun#893][v1 multilora]"
#~ msgstr "[vllm-kunlun#396][multilora][vllm-kunlun#893][v1 multilora]"
#~ msgid "Prompt adapter"
#~ msgstr "提示适配器"
#~ msgid "🔴 No plan"
#~ msgstr "🔴 无计划"
#~ msgid "This feature has been deprecated by vllm."
#~ msgstr "此功能已被 vllm 弃用。"
#~ msgid "Speculative decoding"
#~ msgstr "猜测式解码"
#~ msgid "Basic support"
#~ msgstr "基础支持"
#~ msgid "Pooling"
#~ msgstr "池化"
#~ msgid "🟡 Planned"
#~ msgstr "🟡 计划中"
#~ msgid "CI needed and adapting more models; V1 support rely on vLLM support."
#~ msgstr "需要持续集成CI并适配更多模型V1 的支持依赖于 vLLM 的支持。"
#~ msgid "Enc-dec"
#~ msgstr "Enc-dec编码-解码)"
#~ msgid "🔴 NO plan"
#~ msgstr "🔴 没有计划"
#~ msgid "Plan in 2025.06.30"
#~ msgstr "2025.06.30 的计划"
#~ msgid "Multi Modality"
#~ msgstr "多模态"
#~ msgid "[Tutorial][multimodal], optimizing and adapting more models"
#~ msgstr "[教程][multimodal],优化和适配更多模型"
#~ msgid "LogProbs"
#~ msgstr "LogProbs"
#~ msgid "CI needed"
#~ msgstr "需要持续集成CI"
#~ msgid "Prompt logProbs"
#~ msgstr "提示 logProbs"
#~ msgid "Async output"
#~ msgstr "异步输出"
#~ msgid "Multi step scheduler"
#~ msgstr "多步调度器"
#~ msgid "🔴 Deprecated"
#~ msgstr "🔴 已弃用"
#~ msgid "[vllm#8779][v1_rfc], replaced by [vLLM V1 Scheduler][v1_scheduler]"
#~ msgstr "[vllm#8779][v1_rfc],已被 [vLLM V1 调度器][v1_scheduler] 替代"
#~ msgid "Best of"
#~ msgstr "精选"
#~ msgid "[vllm#13361][best_of], CI needed"
#~ msgstr "[vllm#13361][best_of]需要持续集成CI"
#~ msgid "Beam search"
#~ msgstr "束搜索"
#~ msgid "Guided Decoding"
#~ msgstr "引导解码"
#~ msgid "[vllm-kunlun#177][guided_decoding]"
#~ msgstr "[vllm-kunlun#177][guided_decoding]"
#~ msgid "Tensor Parallel"
#~ msgstr "张量并行"
#~ msgid "Pipeline Parallel"
#~ msgstr "流水线并行"
#~ msgid "Expert Parallel"
#~ msgstr "专家并行"
#~ msgid "CI needed; No plan on V0 support"
#~ msgstr "需要持续集成没有支持V0的计划"
#~ msgid "Data Parallel"
#~ msgstr "数据并行"
#~ msgid "CI needed; No plan on V0 support"
#~ msgstr "需要 CI暂无 V0 支持计划"
#~ msgid "Prefill Decode Disaggregation"
#~ msgstr "预填充 解码 拆分"
#~ msgid "1P1D available, working on xPyD and V1 support."
#~ msgstr "1P1D 已可用,正在开发 xPyD 和 V1 支持。"
#~ msgid "Quantization"
#~ msgstr "量化"
#~ msgid "W8A8 available, CI needed; working on more quantization method support"
#~ msgstr "W8A8 已可用需要持续集成CI正在开发对更多量化方法的支持。"
#~ msgid "Graph Mode"
#~ msgstr "图模式"
#~ msgid "🔵 Experimental"
#~ msgstr "🔵 实验性"
#~ msgid "Experimental, see detail note: [vllm-kunlun#767][graph_mode]"
#~ msgstr "实验性功能,详见说明:[vllm-kunlun#767][graph_mode]"
#~ msgid "Sleep Mode"
#~ msgstr "睡眠模式"
#~ msgid "level=1 available, CI needed, working on V1 support"
#~ msgstr "level=1 可用需要CI正在开发 V1 支持"
#~ msgid "🟢 Functional: Fully operational, with ongoing optimizations."
#~ msgstr "🟢 功能性:完全可用,正在持续优化中。"
#~ msgid ""
#~ "🔵 Experimental: Experimental support, "
#~ "interfaces and functions may change."
#~ msgstr "🔵 实验性:实验性支持,接口和功能可能会发生变化。"
#~ msgid "🚧 WIP: Under active development, will be supported soon."
#~ msgstr "🚧 WIP正在积极开发中很快将会支持。"
#~ msgid ""
#~ "🟡 Planned: Scheduled for future "
#~ "implementation (some may have open "
#~ "PRs/RFCs)."
#~ msgstr "🟡 计划中已安排将来实现其中一些可能已有开放的PR/RFC。"
#~ msgid "🔴 NO plan / Deprecated: No plan for V0 or deprecated by vLLM v1."
#~ msgstr "🔴 没有计划 / 已弃用V0 没有计划或已被 vLLM v1 弃用。"

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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: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\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/user_guide/support_matrix/supported_models.md:1
#, fuzzy
msgid "Supported Models"
msgstr "支持"
#~ msgid "Model Support"
#~ msgstr "模型支持"
#~ msgid "Text-only Language Models"
#~ msgstr "纯文本语言模型"
#~ msgid "Generative Models"
#~ msgstr "生成模型"
#~ msgid "Model"
#~ msgstr "模型"
#~ msgid "Note"
#~ msgstr "注释"
#~ msgid "DeepSeek v3"
#~ msgstr "DeepSeek v3"
#~ msgid "✅"
#~ msgstr "✅"
#~ msgid "DeepSeek R1"
#~ msgstr "DeepSeek R1"
#~ msgid "DeepSeek Distill (Qwen/LLama)"
#~ msgstr "DeepSeek 精炼Qwen/LLama"
#~ msgid "Qwen3"
#~ msgstr "Qwen3"
#~ msgid "Qwen3-Moe"
#~ msgstr "Qwen3-Moe"
#~ msgid "Qwen2.5"
#~ msgstr "Qwen2.5"
#~ msgid "QwQ-32B"
#~ msgstr "QwQ-32B"
#~ msgid "LLama3.1/3.2"
#~ msgstr "LLama3.1/3.2"
#~ msgid "Internlm"
#~ msgstr "Internlm"
#~ msgid "Baichuan"
#~ msgstr "百川"
#~ msgid "Phi-4-mini"
#~ msgstr "Phi-4-mini"
#~ msgid "MiniCPM"
#~ msgstr "MiniCPM"
#~ msgid "MiniCPM3"
#~ msgstr "MiniCPM3"
#~ msgid "LLama4"
#~ msgstr "LLama4"
#~ msgid "Mistral"
#~ msgstr "Mistral"
#~ msgid "Need test"
#~ msgstr "需要测试"
#~ msgid "DeepSeek v2.5"
#~ msgstr "DeepSeek v2.5"
#~ msgid "Gemma-2"
#~ msgstr "Gemma-2"
#~ msgid "Mllama"
#~ msgstr "Mllama"
#~ msgid "Gemma-3"
#~ msgstr "Gemma-3"
#~ msgid "❌"
#~ msgstr "❌"
#~ msgid "[#496](https://github.com/vllm-project/vllm-kunlun/issues/496)"
#~ msgstr "[#496](https://github.com/vllm-project/vllm-kunlun/issues/496)"
#~ msgid "ChatGLM"
#~ msgstr "ChatGLM"
#~ msgid "[#554](https://github.com/vllm-project/vllm-kunlun/issues/554)"
#~ msgstr "[#554](https://github.com/vllm-project/vllm-kunlun/issues/554)"
#~ msgid "Pooling Models"
#~ msgstr "池化模型"
#~ msgid "XLM-RoBERTa-based"
#~ msgstr "基于XLM-RoBERTa"
#~ msgid "Molmo"
#~ msgstr "Molmo"
#~ msgid "Multimodal Language Models"
#~ msgstr "多模态语言模型"
#~ msgid "Qwen2-VL"
#~ msgstr "Qwen2-VL"
#~ msgid "Qwen2.5-VL"
#~ msgstr "Qwen2.5-VL"
#~ msgid "LLaVA 1.5"
#~ msgstr "LLaVA 1.5"
#~ msgid "LLaVA 1.6"
#~ msgstr "LLaVA 1.6"
#~ msgid "[#553](https://github.com/vllm-project/vllm-kunlun/issues/553)"
#~ msgstr "[#553](https://github.com/vllm-project/vllm-kunlun/issues/553)"
#~ msgid "InternVL2"
#~ msgstr "InternVL2"
#~ msgid "InternVL2.5"
#~ msgstr "InternVL2.5"
#~ msgid "Qwen2-Audio"
#~ msgstr "Qwen2-Audio"
#~ msgid "LLaVA-Next"
#~ msgstr "LLaVA-Next"
#~ msgid "LLaVA-Next-Video"
#~ msgstr "LLaVA-Next-Video"
#~ msgid "Phi-3-Vison/Phi-3.5-Vison"
#~ msgstr "Phi-3-Vison/Phi-3.5-Vison"
#~ msgid "GLM-4v"
#~ msgstr "GLM-4v"
#~ msgid "Ultravox"
#~ msgstr "Ultravox"