# 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: 2026-07-17 17:20+0800\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
"Language: pt_BR\n"
"Language-Team: pt_BR <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/backends.rst:5
msgid "Backends"
msgstr "Mecanismo de inferência"

#: ../../source/user_guide/backends.rst:7
msgid ""
"Xinference supports multiple backends for different models. After the "
"user specifies the model, xinference will automatically select the "
"appropriate backend."
msgstr ""
"O Xinference possui diferentes mecanismos de inferência para diferentes "
"modelos. Após o usuário selecionar um modelo, o Xinference escolhe "
"automaticamente o mecanismo adequado."

#: ../../source/user_guide/backends.rst:11
msgid "llama.cpp"
msgstr "llama.cpp"

#: ../../source/user_guide/backends.rst:13
msgid ""
"Xinference now supports `xllamacpp "
"<https://github.com/xorbitsai/xllamacpp>`_ which developed by Xinference "
"team to run llama.cpp backend. `llama.cpp` is developed based on the "
"tensor library `ggml`, supporting inference of the LLaMA series models "
"and their variants."
msgstr ""
"O Xinference atualmente suporta o `xllamacpp "
"<https://github.com/xorbitsai/xllamacpp>`_ desenvolvido pela equipe do "
"Xinference como backend do llama.cpp para execução. O `llama.cpp` é "
"baseado na biblioteca de tensores `ggml` e oferece suporte à inferência "
"de modelos da série LLaMA e suas variações."

#: ../../source/user_guide/backends.rst:20
msgid ""
"Since Xinference v1.5.0, ``xllamacpp`` becomes default option for "
"llama.cpp, and ``llama-cpp-python`` is deprecated. Since Xinference "
"v1.6.0, ``llama-cpp-python`` has been removed."
msgstr ""
"A partir do Xinference v1.5.0, o `xllamacpp` tornou-se a opção padrão "
"para o llama.cpp, e o `llama-cpp-python` foi descontinuado; a partir do "
"Xinference v1.6.0, o `llama-cpp-python` foi removido."

#: ../../source/user_guide/backends.rst:25
msgid "Automatic GPU wheel selection"
msgstr "Seleção automática do wheel de GPU"

#: ../../source/user_guide/backends.rst:29
msgid ""
"When per-model virtual environments are enabled and a usable NVIDIA GPU "
"is present, Xinference automatically installs the ``xllamacpp`` wheel "
"matching the detected CUDA line. CUDA 12.8 and later in the 12.x line use"
" the ``cu128`` wheel index, while CUDA 13.x uses the ``cu132`` wheel "
"index. CPU-only hosts and unsupported CUDA versions keep the default CPU "
"wheel from PyPI. No separate ``xllamacpp`` GPU installation command is "
"required for this launch path."
msgstr "Quando os ambientes virtuais por modelo estão habilitados e há uma GPU NVIDIA utilizável, o Xinference instala automaticamente o wheel ``xllamacpp`` correspondente à linha CUDA detectada. CUDA 12.8 e versões posteriores da série 12.x usam o índice de wheels ``cu128``, enquanto CUDA 13.x usa o índice ``cu132``. Hosts somente com CPU e versões CUDA não compatíveis mantêm o wheel de CPU padrão do PyPI. Esse caminho de inicialização não exige um comando separado de instalação de GPU do ``xllamacpp``."

#: ../../source/user_guide/backends.rst:37
msgid ""
"For all configurable llama.cpp parameters, please refer to the definition"
" of the ``common_params`` structure in ``llama.cpp`` `common.h "
"<https://github.com/ggml-org/llama.cpp/blob/master/common/common.h>`_"
msgstr ""
"Consulte a definição da estrutura `common_params` em `common.h "
"<https://github.com/ggml-org/llama.cpp/blob/master/common/common.h>`_ do "
"``llama.cpp`` para configurar os parâmetros."

#: ../../source/user_guide/backends.rst:39
msgid ""
"There may be some nested parameters. For example, ``sampling.top_k``. "
"Just use the ``.`` to separate nested parameters."
msgstr ""
"Pode haver parâmetros com múltiplos níveis de aninhamento. Por exemplo, "
"``sampling.top_k``. Use ``.`` para separar parâmetros aninhados."

#: ../../source/user_guide/backends.rst:41
msgid "Here is an example of setting nested sampling parameters in WebUI:"
msgstr ""
"Aqui está um exemplo de configuração dos parâmetros de nested sampling na"
" WebUI:"

#: ../../source/user_guide/backends.rst:48
msgid "Auto NGL"
msgstr "NGL automático"

#: ../../source/user_guide/backends.rst:50
msgid ""
"Auto GPU layers estimation is enabled since v1.6.1 when ``n-gpu-layers`` "
"is not specified (default is -1)."
msgstr ""
"Desde v1.6.1, quando n-gpu-layers não é especificado (padrão -1), a "
"estimativa do número de camadas da GPU é ativada automaticamente."

#: ../../source/user_guide/backends.rst:53
msgid ""
"This feature automatically detects the number of GPU layers (NGL) for the"
" llama.cpp backend. Please be aware that this is not an accurate "
"calculation. Therefore, the ``-ngl`` result might not be the most "
"optimized, and there is still a chance of encountering an out-of-memory "
"error."
msgstr ""
"Este recurso pode definir automaticamente o número de camadas de GPU "
"(NGL) para o backend llama.cpp. Observe que não é um cálculo preciso, "
"portanto, o resultado de ``-ngl`` pode não ser ideal e ainda é possível "
"encontrar erros de falta de memória de vídeo."

#: ../../source/user_guide/backends.rst:57
msgid ""
"Currently, there is no official implementation for auto ngl. Please refer"
" to the following issues for more information:"
msgstr ""
"Atualmente, o NGL automático não tem suporte oficial. Consulte a issue "
"abaixo para mais detalhes:"

#: ../../source/user_guide/backends.rst:59
msgid "https://github.com/ggml-org/llama.cpp/issues/13860"
msgstr "https://github.com/ggml-org/llama.cpp/issues/13860"

#: ../../source/user_guide/backends.rst:60
msgid "https://github.com/ggml-org/llama.cpp/pull/6502"
msgstr "https://github.com/ggml-org/llama.cpp/pull/6502"

#: ../../source/user_guide/backends.rst:62
msgid ""
"Our implementation is based on the Ollama auto ngl, but there are some "
"differences:"
msgstr ""
"Nossa implementação é baseada no NGL automático do Ollama, mas com "
"algumas diferenças:"

#: ../../source/user_guide/backends.rst:64
msgid ""
"We utilize device information detected by `xllamacpp "
"<https://github.com/xorbitsai/xllamacpp>`_."
msgstr ""
"Usamos as informações de dispositivo fornecidas pelo `xllamacpp "
"<https://github.com/xorbitsai/xllamacpp>`_."

#: ../../source/user_guide/backends.rst:65
msgid ""
"We have removed support for less popular architectures, these "
"architectures will use the default calculation."
msgstr ""
"Removemos o suporte a algumas arquiteturas incomuns, nas quais a lógica "
"de cálculo padrão era utilizada."

#: ../../source/user_guide/backends.rst:66
msgid ""
"We fall back to offloading all the layers to the GPU if the auto ngl "
"fails."
msgstr "Se a NGL automática falhar, tentaremos carregar tudo na GPU."

#: ../../source/user_guide/backends.rst:67
msgid ""
"We do not support multimodal projectors embedded into the model GGUF, as "
"this is a very experimental feature."
msgstr ""
"Não oferecemos suporte para projetores multimodais incorporados ao GGUF "
"do modelo. Esse formato de modelo ainda está em fase experimental."

#: ../../source/user_guide/backends.rst:71
msgid "Common Issues"
msgstr "Perguntas Frequentes"

#: ../../source/user_guide/backends.rst:73
#, python-brace-format
msgid ""
"**Server error: {'code': 500, 'message': 'failed to process image', "
"'type': 'server_error'}**"
msgstr ""
"**Server error: {'code': 500, 'message': 'failed to process image', "
"'type': 'server_error'}**"

#: ../../source/user_guide/backends.rst:75
#: ../../source/user_guide/backends.rst:99
msgid "The error logs from server:"
msgstr "Log do servidor:"

#: ../../source/user_guide/backends.rst:90
msgid ""
"This could be caused by running out of memory. You can try reducing "
"memory usage by decreasing ``n_ctx``."
msgstr ""
"Pode ser causado por memória insuficiente. Você pode tentar reduzir o "
"``n_ctx`` para resolver."

#: ../../source/user_guide/backends.rst:92
#, python-brace-format
msgid ""
"**Server error: {'code': 400, 'message': 'the request exceeds the "
"available context size. try increasing the context size or enable context"
" shift', 'type': 'invalid_request_error'}**"
msgstr ""
"**Server error: {'code': 400, 'message': 'the request exceeds the "
"available context size. try increasing the context size or enable context"
" shift', 'type': 'invalid_request_error'}**"

#: ../../source/user_guide/backends.rst:94
msgid ""
"If you are using the multimodal feature, the ``ctx_shift`` is disabled by"
" default. Please increase the context size by either increasing ``n_ctx``"
" or reducing ``n_parallel``."
msgstr ""
"Se você estiver usando a funcionalidade multimodal, o ``ctx_shift`` será "
"desativado por padrão. Tente aumentar o ``n_ctx`` ou diminuir o "
"``n_parallel`` para aumentar o tamanho do contexto de cada slot."

#: ../../source/user_guide/backends.rst:97
#, python-brace-format
msgid ""
"**Server error: {'code': 500, 'message': 'Input prompt is too big "
"compared to KV size. Please try increasing KV size.', 'type': "
"'server_error'}**"
msgstr ""
"**Server error: {'code': 500, 'message': 'Input prompt is too big "
"compared to KV size. Please try increasing KV size.', 'type': "
"'server_error'}**"

#: ../../source/user_guide/backends.rst:109
msgid ""
"This could be caused by the KV cache allocation failure. You can try to "
"reduce the context size by either reducing ``n_ctx`` or increasing "
"``n_parallel``, or loading a partial model onto the GPU by adjusting "
"``n_gpu_layers``. Be aware that if you are handling inference requests "
"serially, increasing ``n_parallel`` can't improve the latency or "
"throughput."
msgstr ""
"Isso pode ser causado por falha na criação do cache KV. Você pode "
"resolver reduzindo o `n_ctx`, aumentando o `n_parallel` ou ajustando o "
"parâmetro `n_gpu_layers` para carregar parte do modelo na GPU. Observe "
"que, se você estiver lidando apenas com requisições de inferência serial,"
" aumentar o `n_parallel` não trará ganhos de desempenho."

#: ../../source/user_guide/backends.rst:114
msgid "transformers"
msgstr "transformers"

#: ../../source/user_guide/backends.rst:115
msgid ""
"Transformers supports the inference of most state-of-art models. It is "
"the default backend for models in PyTorch format."
msgstr ""
"O Transformers suporta a grande maioria dos modelos recém-lançados. É o "
"motor padrão usado para modelos no formato Pytorch."

#: ../../source/user_guide/backends.rst:120
msgid "vLLM"
msgstr "vLLM"

#: ../../source/user_guide/backends.rst:121
msgid "vLLM is a fast and easy-to-use library for LLM inference and serving."
msgstr ""
"vLLM é um motor de inferência de modelo de linguagem grande muito "
"eficiente e fácil de usar."

#: ../../source/user_guide/backends.rst:123
msgid "vLLM is fast with:"
msgstr "A vLLM tem as seguintes características:"

#: ../../source/user_guide/backends.rst:125
msgid "State-of-the-art serving throughput"
msgstr "Taxa de transferência de inferência líder"

#: ../../source/user_guide/backends.rst:126
msgid "Efficient management of attention key and value memory with PagedAttention"
msgstr ""
"Uso de PagedAttention para gerenciar eficientemente a memória das chaves "
"e valores de atenção"

#: ../../source/user_guide/backends.rst:127
msgid "Continuous batching of incoming requests"
msgstr "Loteamento contínuo de requisições recebidas"

#: ../../source/user_guide/backends.rst:128
msgid "Optimized CUDA kernels"
msgstr "Kernel CUDA otimizado"

#: ../../source/user_guide/backends.rst:130
msgid ""
"When the following conditions are met, Xinference will choose vLLM as the"
" inference engine:"
msgstr ""
"Quando as seguintes condições forem atendidas, o Xinference selecionará "
"automaticamente o vLLM como mecanismo de inferência:"

#: ../../source/user_guide/backends.rst:132
msgid ""
"The model format is ``pytorch``, ``gptq``, ``awq``, ``fp4``, ``fp8`` or "
"``bnb``."
msgstr ""
"O formato do modelo pode ser ``pytorch``, ``gptq``, ``awq``, ``fp4``, "
"``fp8`` ou ``bnb``."

#: ../../source/user_guide/backends.rst:133
msgid "When the model format is ``pytorch``, the quantization is ``none``."
msgstr ""
"Quando o formato do modelo for ``pytorch``, a opção de quantização deve "
"ser ``none``."

#: ../../source/user_guide/backends.rst:134
msgid "When the model format is ``awq``, the quantization is ``Int4``."
msgstr ""
"Quando o formato do modelo for ``awq``, a opção de quantização deve ser "
"``Int4``."

#: ../../source/user_guide/backends.rst:135
msgid ""
"When the model format is ``gptq``, the quantization is ``Int3``, ``Int4``"
" or ``Int8``."
msgstr ""
"Quando o formato do modelo for ``gptq``, as opções de quantização devem "
"ser ``Int3``, ``Int4`` ou ``Int8``."

#: ../../source/user_guide/backends.rst:136
msgid "The system is Linux and has at least one CUDA device"
msgstr ""
"O sistema operacional é Linux e há pelo menos um dispositivo compatível "
"com CUDA."

#: ../../source/user_guide/backends.rst:137
msgid ""
"The model family (for custom models) / model name (for builtin models) is"
" within the list of models supported by vLLM"
msgstr ""
"Os campos ``model_family`` do modelo personalizado e ``model_name`` do "
"modelo embutido estão na lista de suporte do vLLM."

#: ../../source/user_guide/backends.rst:139
msgid "Currently, supported model includes:"
msgstr "Atualmente, os modelos suportados incluem:"

#: ../../source/user_guide/backends.rst:143
msgid ""
"``code-llama``, ``code-llama-instruct``, ``code-llama-python``, "
"``deepseek``, ``deepseek-chat``, ``deepseek-coder``, ``deepseek-coder-"
"instruct``, ``deepseek-r1-distill-llama``, ``gorilla-openfunctions-v2``, "
"``HuatuoGPT-o1-LLaMA-3.1``, ``llama-2``, ``llama-2-chat``, ``llama-3``, "
"``llama-3-instruct``, ``llama-3.1``, ``llama-3.1-instruct``, "
"``llama-3.3-instruct``, ``minicpm5-1b``, ``tiny-llama``, ``wizardcoder-"
"python-v1.0``, ``wizardmath-v1.0``, ``Yi``, ``Yi-1.5``, ``Yi-1.5-chat``, "
"``Yi-1.5-chat-16k``, ``Yi-200k``, ``Yi-chat``"
msgstr ""
"``code-llama``, ``code-llama-instruct``, ``code-llama-python``, "
"``deepseek``, ``deepseek-chat``, ``deepseek-coder``, ``deepseek-coder-"
"instruct``, ``deepseek-r1-distill-llama``, ``gorilla-openfunctions-v2``, "
"``HuatuoGPT-o1-LLaMA-3.1``, ``llama-2``, ``llama-2-chat``, ``llama-3``, "
"``llama-3-instruct``, ``llama-3.1``, ``llama-3.1-instruct``, "
"``llama-3.3-instruct``, ``minicpm5-1b``, ``tiny-llama``, ``wizardcoder-"
"python-v1.0``, ``wizardmath-v1.0``, ``Yi``, ``Yi-1.5``, ``Yi-1.5-chat``, "
"``Yi-1.5-chat-16k``, ``Yi-200k``, ``Yi-chat``"

#: ../../source/user_guide/backends.rst:144
msgid ""
"``codestral-v0.1``, ``mistral-instruct-v0.1``, ``mistral-instruct-v0.2``,"
" ``mistral-instruct-v0.3``, ``mistral-large-instruct``, ``mistral-nemo-"
"instruct``, ``mistral-v0.1``, ``openhermes-2.5``, ``seallm_v2``"
msgstr ""
"``codestral-v0.1``, ``mistral-instruct-v0.1``, ``mistral-instruct-v0.2``,"
" ``mistral-instruct-v0.3``, ``mistral-large-instruct``, ``mistral-nemo-"
"instruct``, ``mistral-v0.1``, ``openhermes-2.5``, ``seallm_v2``"

#: ../../source/user_guide/backends.rst:145
msgid ""
"``Baichuan-M2``, ``codeqwen1.5``, ``codeqwen1.5-chat``, ``deepseek-r1"
"-distill-qwen``, ``DianJin-R1``, ``fin-r1``, ``HuatuoGPT-o1-Qwen2.5``, "
"``KAT-V1``, ``marco-o1``, ``qwen1.5-chat``, ``qwen2-instruct``, "
"``qwen2.5``, ``qwen2.5-coder``, ``qwen2.5-coder-instruct``, "
"``qwen2.5-instruct``, ``qwen2.5-instruct-1m``, ``qwenLong-l1``, ``QwQ-"
"32B``, ``QwQ-32B-Preview``, ``seallms-v3``, ``skywork-or1``, ``skywork-"
"or1-preview``, ``vibethinker``, ``XiYanSQL-QwenCoder-2504``"
msgstr ""
"``Baichuan-M2``, ``codeqwen1.5``, ``codeqwen1.5-chat``, ``deepseek-r1"
"-distill-qwen``, ``DianJin-R1``, ``fin-r1``, ``HuatuoGPT-o1-Qwen2.5``, "
"``KAT-V1``, ``marco-o1``, ``qwen1.5-chat``, ``qwen2-instruct``, "
"``qwen2.5``, ``qwen2.5-coder``, ``qwen2.5-coder-instruct``, "
"``qwen2.5-instruct``, ``qwen2.5-instruct-1m``, ``qwenLong-l1``, ``QwQ-"
"32B``, ``QwQ-32B-Preview``, ``seallms-v3``, ``skywork-or1``, ``skywork-"
"or1-preview``, ``vibethinker``, ``XiYanSQL-QwenCoder-2504``"

#: ../../source/user_guide/backends.rst:146
msgid "``llama-3.2-vision``, ``llama-3.2-vision-instruct``"
msgstr "``llama-3.2-vision``, ``llama-3.2-vision-instruct``"

#: ../../source/user_guide/backends.rst:147
msgid "``baichuan-2``, ``baichuan-2-chat``"
msgstr "``baichuan-2``, ``baichuan-2-chat``"

#: ../../source/user_guide/backends.rst:148
msgid "``InternLM2ForCausalLM``"
msgstr "``InternLM2ForCausalLM``"

#: ../../source/user_guide/backends.rst:149
msgid "``qwen-chat``"
msgstr "``qwen-chat``"

#: ../../source/user_guide/backends.rst:150
msgid ""
"``mixtral-8x22B-instruct-v0.1``, ``mixtral-instruct-v0.1``, "
"``mixtral-v0.1``"
msgstr ""
"``mixtral-8x22B-instruct-v0.1``, ``mixtral-instruct-v0.1``, "
"``mixtral-v0.1``"

#: ../../source/user_guide/backends.rst:151
msgid "``cogagent``"
msgstr "``cogagent``"

#: ../../source/user_guide/backends.rst:152
msgid "``glm-edge-chat``, ``glm4-chat``, ``glm4-chat-1m``"
msgstr "``glm-edge-chat``, ``glm4-chat``, ``glm4-chat-1m``"

#: ../../source/user_guide/backends.rst:153
msgid "``codegeex4``, ``glm-4v``"
msgstr "``codegeex4``, ``glm-4v``"

#: ../../source/user_guide/backends.rst:154
msgid "``seallm_v2.5``"
msgstr "``seallm_v2.5``"

#: ../../source/user_guide/backends.rst:155
msgid "``orion-chat``"
msgstr "``orion-chat``"

#: ../../source/user_guide/backends.rst:156
msgid "``qwen1.5-moe-chat``, ``qwen2-moe-instruct``"
msgstr "``qwen1.5-moe-chat``, ``qwen2-moe-instruct``"

#: ../../source/user_guide/backends.rst:157
msgid "``CohereForCausalLM``"
msgstr "``CohereForCausalLM``"

#: ../../source/user_guide/backends.rst:158
msgid ""
"``deepseek-v2-chat``, ``deepseek-v2-chat-0628``, ``deepseek-v2.5``, "
"``deepseek-vl2``"
msgstr ""
"``deepseek-v2-chat``, ``deepseek-v2-chat-0628``, ``deepseek-v2.5``, "
"``deepseek-vl2``"

#: ../../source/user_guide/backends.rst:159
msgid ""
"``deepseek-prover-v2``, ``deepseek-r1``, ``deepseek-r1-0528``, "
"``deepseek-v3``, ``deepseek-v3-0324``, ``Deepseek-V3.1``, ``moonlight-"
"16b-a3b-instruct``"
msgstr ""
"``deepseek-prover-v2``, ``deepseek-r1``, ``deepseek-r1-0528``, "
"``deepseek-v3``, ``deepseek-v3-0324``, ``Deepseek-V3.1``, ``moonlight-"
"16b-a3b-instruct``"

#: ../../source/user_guide/backends.rst:160
msgid "``deepseek-r1-0528-qwen3``, ``qwen3``"
msgstr "``deepseek-r1-0528-qwen3``, ``qwen3``"

#: ../../source/user_guide/backends.rst:161
msgid "``minicpm3-4b``"
msgstr "``minicpm3-4b``"

#: ../../source/user_guide/backends.rst:162
msgid "``internlm3-instruct``"
msgstr "``internlm3-instruct``"

#: ../../source/user_guide/backends.rst:163
msgid "``gemma-3-1b-it``"
msgstr "``gemma-3-1b-it``"

#: ../../source/user_guide/backends.rst:164
msgid "``glm4-0414``"
msgstr "``glm4-0414``"

#: ../../source/user_guide/backends.rst:165
msgid ""
"``minicpm-2b-dpo-bf16``, ``minicpm-2b-dpo-fp16``, ``minicpm-2b-dpo-"
"fp32``, ``minicpm-2b-sft-bf16``, ``minicpm-2b-sft-fp32``, ``minicpm4``"
msgstr ""
"``minicpm-2b-dpo-bf16``, ``minicpm-2b-dpo-fp16``, ``minicpm-2b-dpo-"
"fp32``, ``minicpm-2b-sft-bf16``, ``minicpm-2b-sft-fp32``, ``minicpm4``"

#: ../../source/user_guide/backends.rst:166
msgid "``Ernie4.5``"
msgstr "``Ernie4.5``"

#: ../../source/user_guide/backends.rst:167
msgid "``Qwen3-Coder``, ``Qwen3-Instruct``, ``Qwen3-Thinking``"
msgstr "``Qwen3-Coder``, ``Qwen3-Instruct``, ``Qwen3-Thinking``"

#: ../../source/user_guide/backends.rst:168
msgid "``glm-4.5``, ``GLM-4.6``, ``GLM-4.7``"
msgstr "``glm-4.5``, ``GLM-4.6``, ``GLM-4.7``"

#: ../../source/user_guide/backends.rst:169
msgid "``gpt-oss``"
msgstr "``gpt-oss``"

#: ../../source/user_guide/backends.rst:170
msgid "``seed-oss``"
msgstr "``seed-oss``"

#: ../../source/user_guide/backends.rst:171
msgid "``Qwen3-Next-Instruct``, ``Qwen3-Next-Thinking``"
msgstr "``Qwen3-Next-Instruct``, ``Qwen3-Next-Thinking``"

#: ../../source/user_guide/backends.rst:172
msgid "``DeepSeek-V3.2``, ``DeepSeek-V3.2-Exp``"
msgstr "``DeepSeek-V3.2``, ``DeepSeek-V3.2-Exp``"

#: ../../source/user_guide/backends.rst:173
msgid "``MiniMax-M2``, ``MiniMax-M2.5``, ``MiniMax-M2.7``"
msgstr "``MiniMax-M2``, ``MiniMax-M2.5``, ``MiniMax-M2.7``"

#: ../../source/user_guide/backends.rst:174
msgid "``GLM-4.7-Flash``"
msgstr "``GLM-4.7-Flash``"

#: ../../source/user_guide/backends.rst:175
msgid "``glm-5``, ``glm-5.1``"
msgstr "``glm-5``, ``glm-5.1``"

#: ../../source/user_guide/backends.rst:176
msgid "``DeepSeek-V4-Flash``, ``DeepSeek-V4-Pro``"
msgstr ""
"Além de LLMs, o vLLM também pode servir modelos de embedding. Famílias de"
" modelos cujos nomes começam com ``bge``, ``gte``, ``text2vec``, ``m3e``,"
" ``Qwen3`` ou ``bce`` podem ser inicializadas com ``--model-engine vllm``"
" — consulte :ref:`Embeddings <embed>`."

#: ../../source/user_guide/backends.rst:179
msgid ""
"Besides LLMs, vLLM can also serve embedding models. Model families whose "
"names start with ``bge``, ``gte``, ``text2vec``, ``m3e``, ``Qwen3``, or "
"``bce`` can be launched with ``--model-engine vllm`` — see "
":ref:`Embeddings <embed>`."
msgstr ""
"Besides LLMs, vLLM can also serve embedding models. Model families whose "
"names start with ``bge``, ``gte``, ``text2vec``, ``m3e``, ``Qwen3``, or "
"``bce`` can be launched with ``--model-engine vllm`` — see "
":ref:`Embeddings <embed>`."

#: ../../source/user_guide/backends.rst:187
msgid "SGLang"
msgstr "SGLang"

#: ../../source/user_guide/backends.rst:188
msgid ""
"`SGLang <https://github.com/sgl-project/sglang>`_ has a high-performance "
"inference runtime with RadixAttention. It significantly accelerates the "
"execution of complex LLM programs by automatic KV cache reuse across "
"multiple calls. And it also supports other common techniques like "
"continuous batching and tensor parallelism."
msgstr ""
"`SGLang <https://github.com/sgl-project/sgl>`_ possui um runtime de "
"inferência de alto desempenho baseado em RadixAttention. Ele acelera "
"significativamente a execução de programas complexos de LLM ao reutilizar"
" automaticamente o cache KV entre múltiplas chamadas. Também suporta "
"outras técnicas comuns de inferência, como processamento em lote contínuo"
" e paralelismo de tensor."

#: ../../source/user_guide/backends.rst:195
msgid "MLX"
msgstr "MLX"

#: ../../source/user_guide/backends.rst:196
msgid ""
"`MLX <https://github.com/ml-explore/mlx-examples/tree/main/llms>`_ "
"provides efficient runtime to run LLM on Apple silicon. It's recommended "
"to use for Mac users when running on Apple silicon if the model has MLX "
"format support."
msgstr ""
"`MLX <https://github.com/ml-explore/mlx-examples/tree/main/llms>`_ "
"oferece uma maneira eficiente de executar LLMs em chips Apple Silicon. "
"Quando o modelo está no formato MLX, recomenda-se que usuários de Mac com"
" chips Apple Silicon utilizem o motor MLX."

#~ msgid ""
#~ "``code-llama``, ``code-llama-instruct``, "
#~ "``code-llama-python``, ``deepseek``, "
#~ "``deepseek-chat``, ``deepseek-coder``, "
#~ "``deepseek-coder-instruct``, ``deepseek-r1-distill-"
#~ "llama``, ``gorilla-openfunctions-v2``, "
#~ "``HuatuoGPT-o1-LLaMA-3.1``, ``llama-2``, ``llama-2-chat``,"
#~ " ``llama-3``, ``llama-3-instruct``, ``llama-3.1``, "
#~ "``llama-3.1-instruct``, ``llama-3.3-instruct``, ``tiny-"
#~ "llama``, ``wizardcoder-python-v1.0``, "
#~ "``wizardmath-v1.0``, ``Yi``, ``Yi-1.5``, "
#~ "``Yi-1.5-chat``, ``Yi-1.5-chat-16k``, ``Yi-"
#~ "200k``, ``Yi-chat``"
#~ msgstr ""

#~ msgid ""
#~ "``Baichuan-M2``, ``codeqwen1.5``, ``codeqwen1.5-chat``,"
#~ " ``deepseek-r1-distill-qwen``, ``DianJin-R1``, "
#~ "``fin-r1``, ``HuatuoGPT-o1-Qwen2.5``, ``KAT-V1``, "
#~ "``marco-o1``, ``qwen1.5-chat``, ``qwen2-instruct``, "
#~ "``qwen2.5``, ``qwen2.5-coder``, ``qwen2.5-coder-"
#~ "instruct``, ``qwen2.5-instruct``, ``qwen2.5-instruct-"
#~ "1m``, ``qwenLong-l1``, ``QwQ-32B``, ``QwQ-"
#~ "32B-Preview``, ``seallms-v3``, ``skywork-"
#~ "or1``, ``skywork-or1-preview``, ``XiYanSQL-"
#~ "QwenCoder-2504``"
#~ msgstr ""

#~ msgid "``glm-4.5``"
#~ msgstr ""

#~ msgid "``MiniMax-M2``"
#~ msgstr ""
