# 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"
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"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"
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"Generated-By: Babel 2.18.0\n"

#: ../../source/getting_started/troubleshooting.rst:5
msgid "Troubleshooting"
msgstr "Solución de problemas"

#: ../../source/getting_started/troubleshooting.rst:9
msgid "No huggingface repo access"
msgstr "No tienes permisos para el repositorio de Hugging Face."

#: ../../source/getting_started/troubleshooting.rst:11
msgid ""
"Sometimes, you may face errors accessing huggingface models, such as the "
"following message when accessing `llama2`:"
msgstr ""
"Al obtener el modelo, a veces pueden surgir problemas de permisos. Por "
"ejemplo, al obtener el modelo ``llama2`` puede aparecer el siguiente "
"mensaje:"

#: ../../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 ""
"Generalmente, esto se debe a la falta de permisos en el repositorio de "
"Hugging Face o a la ausencia de configuración del token de Hugging Face. "
"Puedes resolver este problema siguiendo los pasos a continuación."

#: ../../source/getting_started/troubleshooting.rst:22
msgid "Get access to the huggingface repo"
msgstr "Solicitar permisos del repositorio de Hugging Face"

#: ../../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 ""
"Para obtener acceso, abre el repositorio correspondiente de Hugging Face y "
"acepta sus términos y condiciones. Tomando como ejemplo ``llama2``, puedes "
"abrir este enlace para solicitarlo: `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 "Configurar credenciales de acceso a Hugging Face"

#: ../../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 ""
"Las credenciales se pueden encontrar en la página de Hugging Face, "
"`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 ""
"Puede configurar las credenciales de acceso estableciendo una variable de "
"entorno, ``export HUGGING_FACE_HUB_TOKEN=your_token_here``."

#: ../../source/getting_started/troubleshooting.rst:37
msgid "Incompatibility Between NVIDIA Driver and PyTorch Version"
msgstr "Controlador de NVIDIA y versión de PyTorch no coinciden"

#: ../../source/getting_started/troubleshooting.rst:39
msgid "If you are using a NVIDIA GPU, you may face the following error:"
msgstr ""
"Si estás utilizando una tarjeta gráfica NVIDIA, es posible que te encuentres"
" con el siguiente error:"

#: ../../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 ""
"Generalmente, esto se debe a que la versión de CUDA es incompatible con la "
"versión de PyTorch."

#: ../../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 ""
"Puede instalar la versión precompilada de PyTorch correspondiente a CUDA "
"desde el sitio web oficial `https://pytorch.org <https://pytorch.org>`_. Al "
"mismo tiempo, **verifique que la versión de CUDA instalada no sea inferior a"
" 11.8, y preferiblemente esté entre 11.8 y 12.1.**"

#: ../../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 ""
"Por ejemplo, si tu versión de CUDA es la 11.8, puedes usar el siguiente "
"comando para instalar PyTorch correspondiente:"

#: ../../source/getting_started/troubleshooting.rst:63
msgid ""
"Xinference service cannot be accessed from external systems through "
"``<IP>:9997``"
msgstr ""
"El sistema externo no puede acceder al servicio Xinference a través de "
"``<IP>:9997``."

#: ../../source/getting_started/troubleshooting.rst:65
msgid "Use ``-H 0.0.0.0`` parameter in when starting Xinference:"
msgstr "Al iniciar Xinference, recuerda agregar el parámetro ``-H 0.0.0.0``:"

#: ../../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 ""
"Entonces el servicio Xinference escuchará en todas las interfaces de red (no"
" solo en ``127.0.0.1`` o ``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 ""
"Si estás usando :ref:`using_docker_image`, agrega ``-p <PORT>:9997`` al "
"comando de ejecución de Docker, y podrás acceder a través de ``<IP>:<PORT>``"
" desde tu máquina local."

#: ../../source/getting_started/troubleshooting.rst:78
msgid ""
"Launching a built-in model takes a long time, and sometimes the model fails "
"to download"
msgstr ""
"Iniciar el modelo integrado requiere mucho tiempo, y a veces la descarga del"
" modelo falla."

#: ../../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 usa HuggingFace como fuente de modelos por defecto. Si tu máquina"
" está en China continental, el uso de modelos integrados puede tener "
"problemas de acceso."

#: ../../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 ""
"Para resolver este problema, puede agregar la variable de entorno "
"`XINFERENCE_MODEL_SRC=modelscope` al iniciar Xinference, cambiando la fuente"
" del modelo a ModelScope, lo que permite una descarga más rápida en China "
"continental."

#: ../../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 ""
"Si estás iniciando Xinference con Docker, puedes incluir la opción ``-e "
"XINFERENCE_MODEL_SRC=modelscope`` en el comando de Docker."

#: ../../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 ""
"Cuando se utiliza la imagen oficial de Docker, RayWorkerVllm muere por OOM, "
"lo que impide cargar el modelo."

#: ../../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 ""
"El parámetro ``--shm-size`` de Docker se puede utilizar para establecer el "
"tamaño de la memoria compartida. El tamaño predeterminado de la memoria "
"compartida (/dev/shm) es de 64 MB, lo que puede no ser suficiente para el "
"backend de vLLM."

#: ../../source/getting_started/troubleshooting.rst:98
msgid ""
"You can increase its size by setting the ``--shm-size`` parameter as "
"follows:"
msgstr "Puede aumentar su tamaño configurando el parámetro ``--shm-size``:"

#: ../../source/getting_started/troubleshooting.rst:106
msgid "Missing ``model_engine`` parameter when launching LLM models"
msgstr ""
"Al cargar el modelo LLM se solicita el parámetro faltante ``model_engine``."

#: ../../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 ""
"A partir de la versión ``v0.11.0``, al cargar el modelo LLM es necesario "
"pasar el parámetro adicional ``model_engine``. Para más información, "
"consulte :ref:`aquí <about_model_engine>`."

#: ../../source/getting_started/troubleshooting.rst:112
msgid "Resolving MKL Threading Layer Conflicts"
msgstr "Resolución de conflictos en la capa de hilos de MKL"

#: ../../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 ""
"Al iniciar el servidor Xinference, si se encuentra el error: ``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 "La causa raíz mostrada en los registros es:"

#: ../../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 ""
"Esto suele deberse a que tu NumPy fue instalado mediante conda, y la versión"
" de NumPy de conda está construida con la optimización Intel MKL, lo que "
"provoca un conflicto con la biblioteca GNU OpenMP (libgomp) ya cargada en el"
" entorno."

#: ../../source/getting_started/troubleshooting.rst:126
msgid "Solution 1: Override the Threading Layer"
msgstr "Solución 1: Reescribir la capa de hilos"

#: ../../source/getting_started/troubleshooting.rst:128
msgid "Force Intel's Math Kernel Library to use GNU's OpenMP implementation:"
msgstr ""
"Establecer MKL_THREADING_LAYER=GNU fuerza a la biblioteca central matemática"
" de Intel (MKL) a usar la implementación de OpenMP de GNU:"

#: ../../source/getting_started/troubleshooting.rst:135
msgid "Solution 2: Reinstall NumPy with pip"
msgstr "Solución 2: Reinstalar NumPy con pip"

#: ../../source/getting_started/troubleshooting.rst:137
msgid "Uninstall conda's NumPy and reinstall using pip:"
msgstr ""
"Desinstala numpy instalado por conda y luego vuelve a instalarlo usando pip."

#: ../../source/getting_started/troubleshooting.rst:146
msgid "Related Note: vLLM and PyTorch"
msgstr "Nota relacionada: vLLM y 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 ""
"Si estás usando vLLM, evita instalar PyTorch a través de conda. Para "
"instrucciones de instalación específicas para tu GPU, consulta la guía "
"oficial de instalación de vLLM: "
"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 "Configurar el espejo de PyPI para acelerar la instalación de paquetes"

#: ../../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 ""
"Si te encuentras en China continental, usar un espejo de PyPI puede acelerar"
" significativamente la velocidad de instalación de paquetes. A continuación "
"se presentan algunas fuentes de espejo comúnmente utilizadas:"

#: ../../source/getting_started/troubleshooting.rst:155
msgid "Tsinghua University: ``https://pypi.tuna.tsinghua.edu.cn/simple``"
msgstr ""
"Espejo de la Universidad de Tsinghua: "
"``https://pypi.tuna.tsinghua.edu.cn/simple``"

#: ../../source/getting_started/troubleshooting.rst:156
msgid "Alibaba Cloud: ``https://mirrors.aliyun.com/pypi/simple/``"
msgstr "Espejo de Alibaba Cloud: ``https://mirrors.aliyun.com/pypi/simple/``"

#: ../../source/getting_started/troubleshooting.rst:157
msgid "Tencent Cloud: ``https://mirrors.cloud.tencent.com/pypi/simple``"
msgstr ""
"Espejo de Tencent Cloud: ``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 ""
"Pero ten en cuenta que algunos espejos pueden carecer de ciertos paquetes. "
"Por ejemplo, si solo usas el espejo de Alibaba Cloud para instalar "
"``xinference[audio]``, la instalación podría fallar."

#: ../../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 ""
"Esto ocurre porque el paquete ``num2words`` del que depende ``MeloTTS`` no "
"está disponible en el mirror de Alibaba Cloud. Por lo tanto, al ejecutar "
"``pip install xinference[audio]``, podría retroceder e instalar una versión "
"anterior, como ``xinference==1.2.0`` y ``xoscar==0.8.0`` (a fecha del 27 de "
"octubre de 2025)."

#: ../../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 ""
"Estas versiones antiguas son incompatibles y causarán el siguiente error: "
"``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 ""
"Para evitar este problema al instalar el paquete de audio de xinference, se "
"recomienda utilizar múltiples fuentes de espejo al mismo tiempo."

#: ../../source/getting_started/troubleshooting.rst:188
msgid "Installing Xinference 1.12.0 with uv Fails (As of November 2025)"
msgstr ""
"Fallo al instalar Xinference 1.12.0 usando uv (hasta noviembre de 2025)"

#: ../../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 ""
"**Nota:** Este es un problema temporal debido al ecosistema de paquetes "
"actual y la estrategia de resolución de dependencias de uv, que prioriza "
"**versiones altas de dependencias directas** en lugar de **versiones de "
"dependencias indirectas**."

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

#: ../../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 ""
"En noviembre de 2025, al instalar xinference 1.12.0 con ``uv pip install "
"xinference``, es posible que encuentres problemas con la instalación de "
"versiones muy antiguas de paquetes dependientes, especialmente:"

#: ../../source/getting_started/troubleshooting.rst:197
msgid "``transformers==4.12.2`` (from 2021)"
msgstr "``transformers==4.12.2`` (procedente de la versión de 2021)"

#: ../../source/getting_started/troubleshooting.rst:198
msgid "``tokenizers==0.10.3`` (from 2021)"
msgstr "``tokenizers==0.10.3`` (de la versión de 2021)"

#: ../../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 ""
"Luego, uv reportó un error: \"Failed to build `tokenizers==0.10.3`\" (fallo "
"al construir `tokenizers==0.10.3`)."

#: ../../source/getting_started/troubleshooting.rst:204
#: ../../source/getting_started/troubleshooting.rst:261
msgid "Root Cause"
msgstr "Causa raíz"

#: ../../source/getting_started/troubleshooting.rst:206
msgid ""
"This occurs because uv prioritizes **higher versions for direct "
"dependencies** over **indirect dependencies**:"
msgstr ""
"El motivo de este problema es que uv prioriza las **versiones más recientes "
"de dependencias directas**, ignorando los requisitos de versión en las "
"**dependencias indirectas**:"

#: ../../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 especifica ``huggingface-hub>=0.19.4`` como **dependencia "
"directa** (sin restricción superior)."

#: ../../source/getting_started/troubleshooting.rst:209
msgid ""
"uv selects the latest: ``huggingface-hub==1.0.1`` as of November 06 2025"
msgstr ""
"Al 6 de noviembre de 2025, uv seleccionará la versión más reciente: "
"``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 ""
"Sin embargo, ``transformers<=4.57.3`` (una **dependencia indirecta** "
"introducida por ``peft``) requiere ``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 ""
"Para resolver el conflicto de dependencias, uv mantuvo la dependencia "
"directa ``huggingface-hub==1.0.1`` y degradó la dependencia indirecta "
"``transformers`` a la versión muy antigua 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 ""
"**Es una característica de diseño de uv**: prioriza las dependencias que "
"especificas explícitamente (dependencias directas) sobre las dependencias "
"transitivas. Enlace de referencia: 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 ""
"**Actualización:** Hasta el 2026.01.05, la versión más reciente de "
"transformers, la 4.57.3, aún depende de ``huggingface-hub<1.0``."

#: ../../source/getting_started/troubleshooting.rst:218
msgid "Solutions"
msgstr "Solución"

#: ../../source/getting_started/troubleshooting.rst:220
msgid "**Solution 1: Pre-constrain huggingface-hub (Recommended)**"
msgstr ""
"**Solución 1: Limitar la versión de huggingface-hub de antemano "
"(recomendado)**"

#: ../../source/getting_started/troubleshooting.rst:222
msgid ""
"Explicitly constrain ``huggingface-hub`` to a compatible version range:"
msgstr ""
"Limita explícitamente ``huggingface-hub`` a un rango de versiones "
"compatible:"

#: ../../source/getting_started/troubleshooting.rst:228
msgid ""
"This forces uv to select a ``huggingface-hub`` version that's compatible "
"with modern ``transformers``."
msgstr ""
"Esto fuerza a uv a seleccionar una versión de ``huggingface-hub`` compatible"
" con la versión moderna de ``transformers``."

#: ../../source/getting_started/troubleshooting.rst:230
msgid "**Solution 2: Make transformers a direct dependency**"
msgstr "**Solución 2: Establecer transformers como dependencia directa**"

#: ../../source/getting_started/troubleshooting.rst:232
msgid ""
"By specifying ``transformers`` explicitly, it becomes a direct dependency "
"and uv will prefer higher versions:"
msgstr ""
"Al especificar explícitamente ``transformers``, se convierte en una "
"dependencia directa, y uv priorizará la versión más reciente:"

#: ../../source/getting_started/troubleshooting.rst:238
msgid "**Solution 3: Use pip**"
msgstr "**Solución 3: Usar pip**"

#: ../../source/getting_started/troubleshooting.rst:240
msgid ""
"Or just resort to using ``pip install xinference`` which will resolve to the"
" following versions"
msgstr ""
"O directamente usa ``pip install xinference``, que resolverá automáticamente"
" la siguiente combinación de versiones:"

#: ../../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 problema de compatibilidad (fallo de segmentación)"

#: ../../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 ""
"Si tienes instalado **vLLM < 0.12.0** y actualizas xinference (especialmente"
" al usar ``uv pip install -U xinference``), es posible que xinference falle "
"al iniciar debido a un error de segmentación:"

#: ../../source/getting_started/troubleshooting.rst:263
msgid "This issue has three contributing factors:"
msgstr "El problema es causado por la combinación de tres factores:"

#: ../../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 ""
"**Incompatibilidad binaria**: vLLM en versiones anteriores a la 0.12.0 fue "
"compilado con PyTorch 2.8.0, y estas versiones son incompatibles con PyTorch"
" 2.9. Referencia: `Notas de lanzamiento de vLLM v0.12.0 "
"<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 ""
"**Dependencia de Torch sin límite superior en Xinference**: En el archivo "
"``pyproject.toml`` de Xinference no se especifica un límite de versión para "
"PyTorch."

#: ../../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 ""
"**Diferencias de comportamiento entre diferentes gestores de paquetes**:"

#: ../../source/getting_started/troubleshooting.rst:279
msgid ""
"**pip**: Conservative - only upgrades the specified package unless "
"dependencies are incompatible"
msgstr ""
"**pip**: es más conservador — solo actualiza las dependencias relacionadas "
"cuando son incompatibles; de lo contrario, solo actualiza el paquete "
"especificado."

#: ../../source/getting_started/troubleshooting.rst:280
msgid ""
"**uv with -U flag**: Aggressive - re-resolves ALL dependencies and picks "
"latest versions"
msgstr ""
"**Usando uv con el parámetro -U**: la estrategia es más agresiva: vuelve a "
"resolver **todas** las dependencias y selecciona la versión más reciente."

#: ../../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 ""
"Por lo tanto, cuando no estés listo para actualizar toda la pila tecnológica"
" y solo quieras actualizar xinference, puedes optar por usar:"

#: ../../source/getting_started/troubleshooting.rst:285
msgid ""
"``pip install -U xinference`` (keeps PyTorch unchanged, only upgrades "
"xinference)"
msgstr ""
"``pip install -U xinference`` (manteniendo la versión de PyTorch sin "
"cambios, solo actualiza 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"
"``` (sin usar el parámetro -U, también solo actualizará xinference)"
