# SOME DESCRIPTIVE TITLE.
# Copyright (C) 2023, Xorbits Inc.
# This file is distributed under the same license as the Xinference package.
# FIRST AUTHOR <EMAIL@ADDRESS>, 2023.
#
#, fuzzy
msgid ""
msgstr ""
"Project-Id-Version: Xinference\n"
"Report-Msgid-Bugs-To: \n"
"POT-Creation-Date: 2026-01-07 15:50+0800\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
"Language-Team: zh_TW <LL@li.org>\n"
"Language: zh_TW\n"
"MIME-Version: 1.0\n"
"Content-Type: text/plain; charset=utf-8\n"
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"Plural-Forms: nplurals=1; plural=0;\n"
"Generated-By: Babel 2.18.0\n"

#: ../../source/getting_started/troubleshooting.rst:5
msgid "Troubleshooting"
msgstr "故障排除"

#: ../../source/getting_started/troubleshooting.rst:9
msgid "No huggingface repo access"
msgstr "沒有 huggingface 倉庫權限"

#: ../../source/getting_started/troubleshooting.rst:11
msgid ""
"Sometimes, you may face errors accessing huggingface models, such as the "
"following message when accessing `llama2`:"
msgstr "獲取模型時，有時候會遇到權限問題。比如在獲取 ``llama2`` 模型時可能會有以下提示："

#: ../../source/getting_started/troubleshooting.rst:18
msgid ""
"This typically indicates either a lack of access rights to the repository or"
" missing huggingface access tokens. The following sections provide guidance "
"on addressing these issues."
msgstr ""
"这种情况通常是缺少 Hugging Face 倉庫的權限，或者是沒有設定 Hugging Face Token。可以按照以下方式解決這個問題。"

#: ../../source/getting_started/troubleshooting.rst:22
msgid "Get access to the huggingface repo"
msgstr "申請 Huggingface 倉庫權限"

#: ../../source/getting_started/troubleshooting.rst:24
msgid ""
"To obtain access, navigate to the desired huggingface repository and agree "
"to its terms and conditions. As an illustration, for the `llama2` model, you"
" can use this link: `https://huggingface.co/meta-llama/Llama-2-7b-hf "
"<https://huggingface.co/meta-llama/Llama-2-7b-hf>`_."
msgstr ""
"想要取得存取權限，請開啟對應的 huggingface 倉庫，同意其條款與注意事項。以 ``llama2`` "
"為例，可以開啟以下連結進行申請：`https://huggingface.co/meta-llama/Llama-2-7b-hf "
"<https://huggingface.co/meta-llama/Llama-2-7b-hf>`_."

#: ../../source/getting_started/troubleshooting.rst:29
msgid "Set up credentials to access huggingface"
msgstr "設定存取 huggingface 憑證"

#: ../../source/getting_started/troubleshooting.rst:31
msgid ""
"Your credential to access huggingface can be found online at "
"`https://huggingface.co/settings/tokens "
"<https://huggingface.co/settings/tokens>`_."
msgstr ""
"可以在 huggingface 頁面找到憑證，`https://huggingface.co/settings/tokens "
"<https://huggingface.co/settings/tokens>`_."

#: ../../source/getting_started/troubleshooting.rst:33
msgid ""
"You can set the token as an environmental variable, with ``export "
"HUGGING_FACE_HUB_TOKEN=your_token_here``."
msgstr "可以透過設定環境變數來設定存取憑證，``export HUGGING_FACE_HUB_TOKEN=your_token_here``。"

#: ../../source/getting_started/troubleshooting.rst:37
msgid "Incompatibility Between NVIDIA Driver and PyTorch Version"
msgstr "NVIDIA 驅動與 PyTorch 版本不匹配"

#: ../../source/getting_started/troubleshooting.rst:39
msgid "If you are using a NVIDIA GPU, you may face the following error:"
msgstr "如果你在使用NVIDIA顯示卡，可能會遇到以下錯誤："

#: ../../source/getting_started/troubleshooting.rst:50
msgid ""
"This typically indicates that your CUDA driver version is not compatible "
"with the PyTorch version you are using."
msgstr "這種情況一般是 CUDA 的版本和 Pytorch 版本不相容導致的。"

#: ../../source/getting_started/troubleshooting.rst:52
msgid ""
"Go to `https://pytorch.org <https://pytorch.org>`_ to install a PyTorch "
"version that has been compiled with your version of the CUDA driver. **Do "
"not install a cuda version smaller than 11.8, preferably between 11.8 and "
"12.1.**"
msgstr ""
"可以到 `https://pytorch.org <https://pytorch.org>`_ 官網安裝和 CUDA 對應的預編譯版本的 "
"PyTorch。同時，**請檢查安裝的 CUDA 版本不要小於 11.8，最好版本在 11.8 到 12.1 之間。**"

#: ../../source/getting_started/troubleshooting.rst:55
msgid ""
"Say if your CUDA driver version is 11.8, then you can install PyTorch with "
"the following command:"
msgstr "例如你的 CUDA 版本是 11.8，可以使用以下指令安裝對應的 PyTorch："

#: ../../source/getting_started/troubleshooting.rst:63
msgid ""
"Xinference service cannot be accessed from external systems through "
"``<IP>:9997``"
msgstr "外部系統無法透過 ``<IP>:9997`` 存取 Xinference 服務"

#: ../../source/getting_started/troubleshooting.rst:65
msgid "Use ``-H 0.0.0.0`` parameter in when starting Xinference:"
msgstr "在啟動 Xinference 時記得要加上 ``-H 0.0.0.0`` 參數:"

#: ../../source/getting_started/troubleshooting.rst:71
msgid ""
"Then Xinference service will listen on all network interfaces (not limited "
"to ``127.0.0.1`` or ``localhost``)."
msgstr "那麼 Xinference 服務將監聽所有網路介面（而不僅限於 ``127.0.0.1`` 或 ``localhost``）。"

#: ../../source/getting_started/troubleshooting.rst:73
msgid ""
"If you are using the :ref:`using_docker_image`, please add ``-p "
"<PORT>:9997`` during the docker run command, then access is available "
"through ``<IP>:<PORT>`` of the local machine."
msgstr ""
"如果使用的是 :ref:`using_docker_image`，請在 Docker 運行命令中加上 ``-p "
"<PORT>:9997``，你就可以透過本地機器的 ``<IP>:<PORT>`` 進行存取。"

#: ../../source/getting_started/troubleshooting.rst:78
msgid ""
"Launching a built-in model takes a long time, and sometimes the model fails "
"to download"
msgstr "啟動內建模型需要很長時間，模型有時下載失敗"

#: ../../source/getting_started/troubleshooting.rst:80
msgid ""
"Xinference by default uses HuggingFace as the source for models. If your "
"machines are in Mainland China, there might be accessibility issues when "
"using built-in models."
msgstr "Xinference 預設使用 HuggingFace 作為模型來源。如果你的機器在中國大陸，使用內建模型可能會遇到存取問題。"

#: ../../source/getting_started/troubleshooting.rst:84
msgid ""
"To address this, add environment variable "
"``XINFERENCE_MODEL_SRC=modelscope`` when starting the Xinference to change "
"the model source to ModelScope, which is optimized for Mainland China."
msgstr ""
"要解決這個問題，可以在啟動 Xinference 時添加環境變數 "
"``XINFERENCE_MODEL_SRC=modelscope``，將模型來源更改為 ModelScope，在中國大陸下載速度更快。"

#: ../../source/getting_started/troubleshooting.rst:88
msgid ""
"If you’re starting Xinference with Docker, include ``-e "
"XINFERENCE_MODEL_SRC=modelscope`` during the docker run command."
msgstr ""
"如果你用 Docker 啟動 Xinference，可以在 Docker 命令中包含 ``-e "
"XINFERENCE_MODEL_SRC=modelscope`` 選項。"

#: ../../source/getting_started/troubleshooting.rst:92
msgid ""
"When using the official Docker image, RayWorkerVllm died due to OOM, causing"
" the model to fail to load"
msgstr "使用官方 Docker 映像時，RayWorkerVllm 因 OOM 而死亡，導致模型無法載入"

#: ../../source/getting_started/troubleshooting.rst:94
msgid ""
"Docker's ``--shm-size`` parameter is used to set the size of shared memory. "
"The default size of shared memory (/dev/shm) is 64MB, which may be too small"
" for vLLM backend."
msgstr ""
"Docker 的 ``--shm-size`` 參數可以用來設定共享記憶體的大小。共享記憶體(/dev/shm)的預設大小是 64MB，對於 vLLM "
"後端來說可能不夠。"

#: ../../source/getting_started/troubleshooting.rst:98
msgid ""
"You can increase its size by setting the ``--shm-size`` parameter as "
"follows:"
msgstr "你可以透過設定參數 ``--shm-size`` 來增加它的大小："

#: ../../source/getting_started/troubleshooting.rst:106
msgid "Missing ``model_engine`` parameter when launching LLM models"
msgstr "載入 LLM 模型時提示缺少 ``model_engine`` 參數"

#: ../../source/getting_started/troubleshooting.rst:108
msgid ""
"Since version ``v0.11.0``, launching LLM models requires an additional "
"``model_engine`` parameter. For specific information, please refer to "
":ref:`here <about_model_engine>`."
msgstr ""
"自 ``v0.11.0`` 版本開始，載入 LLM 模型時需要傳入額外參數 ``model_engine`` 。具體資訊請參考 :ref:`這裡 "
"<about_model_engine>` 。"

#: ../../source/getting_started/troubleshooting.rst:112
msgid "Resolving MKL Threading Layer Conflicts"
msgstr "解決 MKL 執行緒層衝突"

#: ../../source/getting_started/troubleshooting.rst:114
msgid ""
"When starting the Xinference server, you may encounter the error: "
"``ValueError: Model architectures ['Qwen2ForCausalLM'] failed to be "
"inspected. Please check the logs for more details.``"
msgstr ""
"在啟動 Xinference 伺服器時，如果遇到錯誤：``ValueError: Model architectures "
"['Qwen2ForCausalLM'] failed to be inspected. . Please check the logs for "
"more details.``"

#: ../../source/getting_started/troubleshooting.rst:116
msgid "The underlying cause shown in the logs is:"
msgstr "日誌中顯示的根本原因是："

#: ../../source/getting_started/troubleshooting.rst:123
msgid ""
"This typically occurs when NumPy was installed via conda. Conda's NumPy is "
"built with Intel MKL optimizations, which conflicts with the GNU OpenMP "
"library (libgomp) already loaded in your environment."
msgstr ""
"這通常是因為你的 NumPy 是透過 conda 安裝的，而 conda 的 NumPy 是使用 Intel MKL "
"最佳化構建的，這導致它與環境中已載入的 GNU OpenMP 庫（libgomp）產生衝突。"

#: ../../source/getting_started/troubleshooting.rst:126
msgid "Solution 1: Override the Threading Layer"
msgstr "解決方案 1：重寫執行緒層"

#: ../../source/getting_started/troubleshooting.rst:128
msgid "Force Intel's Math Kernel Library to use GNU's OpenMP implementation:"
msgstr "設定 MKL_THREADING_LAYER=GNU 可以強制 Intel 數學核心庫（MKL）使用 GNU 的 OpenMP 實現："

#: ../../source/getting_started/troubleshooting.rst:135
msgid "Solution 2: Reinstall NumPy with pip"
msgstr "解決方案 2：使用 pip 重新安裝 NumPy"

#: ../../source/getting_started/troubleshooting.rst:137
msgid "Uninstall conda's NumPy and reinstall using pip:"
msgstr "卸載 conda 安裝的 numpy，然後使用 pip 重新安裝。"

#: ../../source/getting_started/troubleshooting.rst:146
msgid "Related Note: vLLM and PyTorch"
msgstr "相關說明：vLLM 與 PyTorch"

#: ../../source/getting_started/troubleshooting.rst:148
msgid ""
"If you're using vLLM, avoid installing PyTorch with conda. Refer to the "
"official vLLM installation guide for GPU-specific instructions: "
"https://docs.vllm.ai/en/latest/getting_started/installation/gpu.html"
msgstr ""
"如果你在使用 vLLM，請避免透過 conda 安裝 PyTorch。有關特定 GPU 的安裝說明，請參閱 vLLM "
"官方安裝指南：https://docs.vllm.ai/en/latest/getting_started/installation/gpu.html"

#: ../../source/getting_started/troubleshooting.rst:151
msgid "Configuring PyPI Mirrors to Speed Up Package Installation"
msgstr "配置 PyPI 鏡像以加快軟體套件安裝速度"

#: ../../source/getting_started/troubleshooting.rst:153
msgid ""
"If you're in Mainland China, using a PyPI mirror can significantly speed up "
"package installation. Here are some commonly used mirrors:"
msgstr "如果你在中國大陸，使用 PyPI 鏡像可以顯著加快軟體套件的安裝速度。以下是一些常用的鏡像源："

#: ../../source/getting_started/troubleshooting.rst:155
msgid "Tsinghua University: ``https://pypi.tuna.tsinghua.edu.cn/simple``"
msgstr "清華大學鏡像：``https://pypi.tuna.tsinghua.edu.cn/simple``"

#: ../../source/getting_started/troubleshooting.rst:156
msgid "Alibaba Cloud: ``https://mirrors.aliyun.com/pypi/simple/``"
msgstr "阿里雲鏡像：``https://mirrors.aliyun.com/pypi/simple/``"

#: ../../source/getting_started/troubleshooting.rst:157
msgid "Tencent Cloud: ``https://mirrors.cloud.tencent.com/pypi/simple``"
msgstr "騰訊雲鏡像：``https://mirrors.cloud.tencent.com/pypi/simple``"

#: ../../source/getting_started/troubleshooting.rst:159
msgid ""
"However, be aware that some packages may not be available on certain "
"mirrors. For example, if you're installing ``xinference[audio]`` using only "
"the Aliyun mirror, the installation may fail."
msgstr "但請注意，某些映像源上可能缺少部分軟體套件。例如，如果你僅使用阿里雲映像安裝 ``xinference[audio]``，安裝可能會失敗。"

#: ../../source/getting_started/troubleshooting.rst:161
msgid ""
"This happens because ``num2words``, a dependency used by ``MeloTTS``, is not"
" available on the Aliyun mirror. As a result, ``pip install "
"xinference[audio]`` will resolve to older versions like "
"``xinference==1.2.0`` and ``xoscar==0.8.0`` (as of Oct 27, 2025)."
msgstr ""
"這是因為 ``MeloTTS`` 所依賴的 ``num2words`` 軟體套件在阿里雲鏡像上不可用。因此，在執行 ``pip install "
"xinference[audio]`` 時，可能會回退安裝舊版本，例如 ``xinference==1.2.0`` 和 "
"``xoscar==0.8.0`` （截至 2025 年 10 月 27 日）。"

#: ../../source/getting_started/troubleshooting.rst:163
msgid ""
"These older versions are incompatible and will produce the error: "
"``MainActorPool.append_sub_pool() got an unexpected keyword argument "
"'start_method'``"
msgstr ""
"這些舊版本不相容，會導致以下錯誤：``MainActorPool.append_sub_pool() got an unexpected keyword"
" argument 'start_method'``"

#: ../../source/getting_started/troubleshooting.rst:174
msgid ""
"To avoid this issue when installing the xinference audio package, use "
"multiple mirrors:"
msgstr "為避免在安裝 xinference 音訊套件時出現此問題，建議同時使用多個映像來源："

#: ../../source/getting_started/troubleshooting.rst:188
msgid "Installing Xinference 1.12.0 with uv Fails (As of November 2025)"
msgstr "使用 uv 安裝 Xinference 1.12.0 失敗（截至 2025 年 11 月）"

#: ../../source/getting_started/troubleshooting.rst:190
msgid ""
"**Note:** This is a temporary issue due to the current package ecosystem and"
" uv prioritizing **higher versions for direct dependencies** over **indirect"
" dependencies**."
msgstr ""
"**注意：** 這是一個暫時性的問題，原因在於目前的軟體套件生態系統以及 uv 的依賴解析策略——它會優先選擇 **直接依賴的高版本**，而不是 "
"**間接依賴的版本**。"

#: ../../source/getting_started/troubleshooting.rst:193
#: ../../source/getting_started/troubleshooting.rst:250
msgid "Symptom"
msgstr "症狀"

#: ../../source/getting_started/troubleshooting.rst:195
msgid ""
"When installing xinference 1.12.0 as of November 2025 using ``uv pip install"
" xinference``, you may encounter an issue where very old package versions "
"are installed, particularly:"
msgstr ""
"在 2025 年 11 月使用 ``uv pip install xinference`` 安裝 xinference 1.12.0 "
"時，你可能會遇到安裝到非常舊版本依賴套件的問題，尤其是："

#: ../../source/getting_started/troubleshooting.rst:197
msgid "``transformers==4.12.2`` (from 2021)"
msgstr "``transformers==4.12.2`` （來自 2021 年的版本）"

#: ../../source/getting_started/troubleshooting.rst:198
msgid "``tokenizers==0.10.3`` (from 2021)"
msgstr "``tokenizers==0.10.3`` （來自 2021 年的版本）"

#: ../../source/getting_started/troubleshooting.rst:199
msgid "``huggingface-hub==1.0.1``"
msgstr ""

#: ../../source/getting_started/troubleshooting.rst:201
msgid "Then uv fails with \"Failed to build `tokenizers==0.10.3`\""
msgstr ""
"隨後 uv 報錯：\"Failed to build `tokenizers==0.10.3`\"（建置 `tokenizers==0.10.3` "
"失敗）"

#: ../../source/getting_started/troubleshooting.rst:204
#: ../../source/getting_started/troubleshooting.rst:261
msgid "Root Cause"
msgstr "根本原因"

#: ../../source/getting_started/troubleshooting.rst:206
msgid ""
"This occurs because uv prioritizes **higher versions for direct "
"dependencies** over **indirect dependencies**:"
msgstr "出現該問題的原因是 uv 會優先選擇 **直接依賴的高版本**，而忽略 **間接依賴** 中的版本要求："

#: ../../source/getting_started/troubleshooting.rst:208
msgid ""
"xinference 1.12.0 specifies ``huggingface-hub>=0.19.4`` as a **direct "
"dependency** (no upper bound)"
msgstr "xinference 1.12.0 將 ``huggingface-hub>=0.19.4`` 指定為 **直接依賴** （沒有上限約束）"

#: ../../source/getting_started/troubleshooting.rst:209
msgid ""
"uv selects the latest: ``huggingface-hub==1.0.1`` as of November 06 2025"
msgstr "截至 2025 年 11 月 6 日，uv 會選擇最新版本：``huggingface-hub==1.0.1``"

#: ../../source/getting_started/troubleshooting.rst:210
msgid ""
"However, ``transformers<=4.57.3`` (an **indirect dependency** via ``peft``) "
"requires ``huggingface-hub<1.0``"
msgstr ""
"然而，``transformers<=4.57.3`` （透過 ``peft`` 引入的 **間接依賴** ）要求 ``huggingface-"
"hub<1.0``"

#: ../../source/getting_started/troubleshooting.rst:211
msgid ""
"To resolve the conflict, uv keeps the direct dependency at 1.0.1 and "
"downgrades the indirect dependency ``transformers`` to ancient version "
"4.12.2"
msgstr ""
"為了解決依賴衝突，uv 保留了直接依賴 ``huggingface-hub==1.0.1``，並將間接依賴 ``transformers`` "
"降級到了非常舊的版本 4.12.2。"

#: ../../source/getting_started/troubleshooting.rst:213
msgid ""
"**This is by design in uv**: it prioritizes what you explicitly ask for "
"(direct dependencies) over transitive dependencies. Refer to "
"https://github.com/astral-sh/uv/issues/16601"
msgstr ""
"**這屬於 uv "
"的設計特性**：它會優先滿足你明確指定的相依項目（直接相依），而非遞迴相依。參考連結：https://github.com/astral-"
"sh/uv/issues/16601"

#: ../../source/getting_started/troubleshooting.rst:215
msgid ""
"**Update:** The latest transformers 4.57.3 (as in 2026.01.05) still requires"
" ``huggingface-hub<1.0``."
msgstr ""
"**更新：** 截至 2026.01.05，transformers 最新版本 4.57.3 依然 依賴 ``huggingface-"
"hub<1.0``。"

#: ../../source/getting_started/troubleshooting.rst:218
msgid "Solutions"
msgstr "解決方案"

#: ../../source/getting_started/troubleshooting.rst:220
msgid "**Solution 1: Pre-constrain huggingface-hub (Recommended)**"
msgstr "**解決方案 1：預先限定 huggingface-hub 版本（推薦）**"

#: ../../source/getting_started/troubleshooting.rst:222
msgid ""
"Explicitly constrain ``huggingface-hub`` to a compatible version range:"
msgstr "顯式地將 ``huggingface-hub`` 限定在一個相容的版本範圍內："

#: ../../source/getting_started/troubleshooting.rst:228
msgid ""
"This forces uv to select a ``huggingface-hub`` version that's compatible "
"with modern ``transformers``."
msgstr "這樣可以強制 uv 選擇與現代版本 ``transformers`` 相容的 ``huggingface-hub`` 版本。"

#: ../../source/getting_started/troubleshooting.rst:230
msgid "**Solution 2: Make transformers a direct dependency**"
msgstr "**解決方案 2：將 transformers 設為直接依賴**"

#: ../../source/getting_started/troubleshooting.rst:232
msgid ""
"By specifying ``transformers`` explicitly, it becomes a direct dependency "
"and uv will prefer higher versions:"
msgstr "透過明確指定 ``transformers``，它會成為直接依賴，uv 將優先選擇更高版本："

#: ../../source/getting_started/troubleshooting.rst:238
msgid "**Solution 3: Use pip**"
msgstr "**解決方案 3：使用 pip**"

#: ../../source/getting_started/troubleshooting.rst:240
msgid ""
"Or just resort to using ``pip install xinference`` which will resolve to the"
" following versions"
msgstr "或者直接使用 ``pip install xinference``，它會自動解析到以下版本組合："

#: ../../source/getting_started/troubleshooting.rst:242
msgid "``transformers==4.57.1``"
msgstr ""

#: ../../source/getting_started/troubleshooting.rst:243
msgid "``huggingface-hub==0.36.0``"
msgstr ""

#: ../../source/getting_started/troubleshooting.rst:244
msgid "``tokenizers==0.22.1``"
msgstr ""

#: ../../source/getting_started/troubleshooting.rst:247
msgid "vLLM + Torch + Xinference Compatibility Issue (Segmentation Fault)"
msgstr "vLLM + Torch + Xinference 相容性問題（段錯誤）"

#: ../../source/getting_started/troubleshooting.rst:252
msgid ""
"If you have **vLLM < 0.12.0** installed and upgrade xinference (particularly"
" using ``uv pip install -U xinference``), xinference may fail to start with "
"a segmentation fault:"
msgstr ""
"若您安裝的是 **vLLM < 0.12.0**，且已升級 xinference（特別是使用 ``uv pip install -U "
"xinference`` 時），xinference 可能在啟動時因區段錯誤而失敗："

#: ../../source/getting_started/troubleshooting.rst:263
msgid "This issue has three contributing factors:"
msgstr "該問題由三個因素共同導致："

#: ../../source/getting_started/troubleshooting.rst:265
msgid ""
"**Binary Incompatibility**: vLLM versions before 0.12.0 were compiled "
"against PyTorch 2.8.0. These versions are incompatible with PyTorch 2.9. "
"Reference: `vLLM v0.12.0 Release Notes <https://github.com/vllm-"
"project/vllm/releases/tag/v0.12.0>`_"
msgstr ""
"**二進位不相容性**：vLLM 在 0.12.0 之前的版本是基於 PyTorch 2.8.0 編譯的，這些版本與 PyTorch 2.9 "
"不相容。參考：`vLLM v0.12.0 發布說明 <https://github.com/vllm-"
"project/vllm/releases/tag/v0.12.0>`_"

#: ../../source/getting_started/troubleshooting.rst:267
msgid ""
"**Xinference's Unbounded Torch Dependency**: Xinference's "
"``pyproject.toml`` does not specify an upper bound for PyTorch:"
msgstr ""
"**Xinference 對 Torch 依賴未設定上限**：Xinference 的 ``pyproject.toml`` 中未為 PyTorch "
"指定版本上限："

#: ../../source/getting_started/troubleshooting.rst:275
msgid ""
"This allows package managers to upgrade PyTorch to incompatible versions."
msgstr ""

#: ../../source/getting_started/troubleshooting.rst:277
msgid "**Different Package Manager Behaviors**:"
msgstr "**不同套件管理員的行為差異**："

#: ../../source/getting_started/troubleshooting.rst:279
msgid ""
"**pip**: Conservative - only upgrades the specified package unless "
"dependencies are incompatible"
msgstr "**pip**：較為保守 —— 僅在相依性不相容時，才會升級相關相依性，否則只升級指定的套件。"

#: ../../source/getting_started/troubleshooting.rst:280
msgid ""
"**uv with -U flag**: Aggressive - re-resolves ALL dependencies and picks "
"latest versions"
msgstr "**使用 -U 參數的 uv**：策略較為激進 —— 會重新解析**所有**依賴，並選擇最新版本"

#: ../../source/getting_started/troubleshooting.rst:283
msgid ""
"Therefore before you're ready to upgrade your entire stack and just want to "
"upgrade xinference, use either:"
msgstr "因此，在你尚未準備好升級整個技術棧、而只是想升級 xinference 時，可以選擇使用："

#: ../../source/getting_started/troubleshooting.rst:285
msgid ""
"``pip install -U xinference`` (keeps PyTorch unchanged, only upgrades "
"xinference)"
msgstr ""
"```\n"
"pip install -U xinference\n"
"``` （保持 PyTorch 版本不變，僅升級 xinference）"

#: ../../source/getting_started/troubleshooting.rst:286
msgid ""
"``uv pip install \"xinference==1.16.0\"`` (without -U flag, only upgrades "
"xinference too)"
msgstr ""
"```\n"
"uv pip install \"xinference==1.16.0\"\n"
"```（不使用 -U 參數，同樣只會升級 xinference）"
