javadandCursor
b93ecf1691
Keep source, config, and deploy files. Leave runtime data, uploads, and logs out of git. Co-authored-by: Cursor <cursoragent@cursor.com>
1126 lines
47 KiB
Gettext
1126 lines
47 KiB
Gettext
# French translations for PACKAGE package.
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# Copyright (C) 2025 THE PACKAGE'S COPYRIGHT HOLDER
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# This file is distributed under the same license as the PACKAGE package.
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# Automatically generated, 2025.
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#
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msgid ""
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msgstr ""
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"Project-Id-Version: PACKAGE VERSION\n"
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"Report-Msgid-Bugs-To: \n"
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"POT-Creation-Date: 2025-03-19 00:06+0800\n"
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"PO-Revision-Date: 2025-02-23 13:40+0800\n"
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"Last-Translator: Automatically generated\n"
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"Language-Team: none\n"
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"Language: fr\n"
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"MIME-Version: 1.0\n"
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"Content-Type: text/plain; charset=UTF-8\n"
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"Content-Transfer-Encoding: 8bit\n"
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"Plural-Forms: nplurals=2; plural=(n > 1);\n"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/siliconflow.py:32
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msgid "SiliconFlow Proxy LLM"
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msgstr "LLM proxy SiliconFlow"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/siliconflow.py:35
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msgid "SiliconFlow proxy LLM configuration."
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msgstr "Configuration du LLM proxy SiliconFlow."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/siliconflow.py:48
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msgid "The base url of the SiliconFlow API."
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msgstr "L'URL de base de l'API SiliconFlow."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/siliconflow.py:55
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msgid "The API key of the SiliconFlow API."
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msgstr "La clé API de l'API SiliconFlow."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/chatgpt.py:35
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/chatgpt.py:38
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msgid "OpenAI Compatible Proxy LLM"
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msgstr "LLM proxy compatible avec OpenAI"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/chatgpt.py:51
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msgid "The base url of the OpenAI API."
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msgstr "L'URL de base de l'API OpenAI."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/chatgpt.py:58
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msgid "The API key of the OpenAI API."
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msgstr "La clé API de l'API OpenAI."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/chatgpt.py:65
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msgid "The type of the OpenAI API, if you use Azure, it can be: azure"
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msgstr "Le type de l'API OpenAI, si vous utilisez Azure, il peut être : azure"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/chatgpt.py:71
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msgid "The version of the OpenAI API."
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msgstr "La version de l'API OpenAI."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/chatgpt.py:78
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/wenxin.py:78
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msgid ""
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"The context length of the OpenAI API. If None, it is determined by the model."
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msgstr ""
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"La longueur du contexte de l'API OpenAI. Si None, elle est déterminée par le "
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"modèle."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/chatgpt.py:86
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msgid "The http or https proxy to use openai"
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msgstr "Le proxy http ou https à utiliser pour OpenAI"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/chatgpt.py:90
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/wenxin.py:85
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#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:278
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#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:43
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msgid "Model concurrency limit"
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msgstr "Limite de concurrence du modèle"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/chatgpt.py:104
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msgid "OpenAI LLM Client"
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msgstr "Client LLM OpenAI"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/chatgpt.py:109
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msgid "OpenAI API Key"
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msgstr "Clé API OpenAI"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/chatgpt.py:115
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msgid ""
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"OpenAI API Key, not required if you have set OPENAI_API_KEY environment "
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"variable."
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msgstr ""
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"Clé API OpenAI, non requise si vous avez défini la variable d'environnement "
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"OPENAI_API_KEY."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/chatgpt.py:120
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msgid "OpenAI API Base"
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msgstr "Base API OpenAI"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/chatgpt.py:126
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msgid ""
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"OpenAI API Base, not required if you have set OPENAI_API_BASE environment "
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"variable."
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msgstr ""
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"Base API OpenAI, non requise si vous avez défini la variable d'environnement "
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"OPENAI_API_BASE."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/zhipu.py:31
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msgid "Zhipu Proxy LLM"
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msgstr "Zhipu Proxy LLM"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/zhipu.py:34
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msgid "Zhipu proxy LLM configuration."
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msgstr "Configuration du proxy LLM Zhipu."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/zhipu.py:47
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msgid "The base url of the Zhipu API."
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msgstr "L'URL de base de l'API Zhipu."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/zhipu.py:54
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msgid "The API key of the Zhipu API."
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msgstr "La clé API de l'API Zhipu."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/moonshot.py:31
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msgid "Moonshot Proxy LLM"
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msgstr "Moonshot Proxy LLM"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/moonshot.py:47
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msgid "The base url of the Moonshot API."
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msgstr "L'URL de base de l'API Moonshot."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/moonshot.py:54
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msgid "The API key of the Moonshot API."
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msgstr "La clé API de l'API Moonshot."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/gitee.py:32
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msgid "Gitee Proxy LLM"
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msgstr "Gitee Proxy LLM"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/gitee.py:48
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msgid "The base url of the Gitee API."
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msgstr "L'URL de base de l'API Gitee."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/gitee.py:55
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msgid "The API key of the Gitee API."
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msgstr "La clé API de l'API Gitee."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/deepseek.py:32
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msgid "Deepseek Proxy LLM"
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msgstr "Deepseek Proxy LLM"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/deepseek.py:35
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msgid "Deepseek proxy LLM configuration."
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msgstr "Configuration du proxy LLM Deepseek."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/deepseek.py:48
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msgid "The base url of the DeepSeek API."
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msgstr "L'URL de base de l'API DeepSeek."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/deepseek.py:55
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msgid "The API key of the DeepSeek API."
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msgstr "La clé API de l'API DeepSeek."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/ollama.py:30
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msgid "Ollama Proxy LLM"
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msgstr "Ollama Proxy LLM"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/ollama.py:33
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msgid "Ollama proxy LLM configuration."
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msgstr "Configuration du proxy LLM Ollama."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/ollama.py:46
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msgid "The base url of the Ollama API."
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msgstr "L'URL de base de l'API Ollama."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/yi.py:31
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msgid "Yi Proxy LLM"
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msgstr "Yi Proxy LLM"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/yi.py:47
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msgid "The base url of the Yi API."
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msgstr "L'URL de base de l'API Yi."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/yi.py:54
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msgid "The API key of the Yi API."
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msgstr "La clé API de l'API Yi."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/spark.py:26
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msgid "Xunfei Spark Proxy LLM"
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msgstr "Xunfei Spark Proxy LLM"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/spark.py:42
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msgid "The base url of the Spark API."
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msgstr "L'URL de base de l'API Spark."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/spark.py:49
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msgid "The API key of the Spark API."
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msgstr "La clé API de l'API Spark."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/baichuan.py:31
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/baichuan.py:34
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msgid "Baichuan Proxy LLM"
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msgstr "Baichuan Proxy LLM"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/baichuan.py:47
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msgid "The base url of the Baichuan API."
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msgstr "L'URL de base de l'API Baichuan."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/baichuan.py:54
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msgid "The API key of the Baichuan API."
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msgstr "La clé API de l'API Baichuan."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/gemini.py:50
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msgid "Gemini Proxy LLM"
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msgstr "Gemini Proxy LLM"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/gemini.py:53
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msgid "Google Gemini proxy LLM configuration."
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msgstr "Configuration du proxy LLM Google Gemini."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/gemini.py:66
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msgid "The base url of the gemini API."
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msgstr "L'URL de base de l'API Gemini."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/gemini.py:73
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msgid "The API key of the gemini API."
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msgstr "La clé API de l'API Gemini."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/tongyi.py:36
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msgid "Tongyi Proxy LLM"
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msgstr "Tongyi Proxy LLM"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/tongyi.py:39
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msgid "Tongyi proxy LLM configuration."
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msgstr "Configuration du proxy LLM Tongyi."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/tongyi.py:52
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msgid "The base url of the tongyi API."
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msgstr "L'URL de base de l'API Tongyi."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/tongyi.py:59
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msgid "The API key of the tongyi API."
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msgstr "La clé API de l'API Tongyi."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/volcengine.py:31
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msgid "Volcengine Proxy LLM"
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msgstr "LLM proxy Volcengine"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/volcengine.py:34
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msgid "Volcengine proxy LLM configuration."
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msgstr "Configuration du LLM proxy Volcengine."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/volcengine.py:47
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msgid "The base url of the Volcengine API."
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msgstr "L'URL de base de l'API Volcengine."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/volcengine.py:54
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msgid "The API key of the Volcengine API."
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msgstr "La clé API de l'API Volcengine."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/wenxin.py:46
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msgid "Baidu Wenxin Proxy LLM"
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msgstr "LLM proxy Baidu Wenxin"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/wenxin.py:49
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msgid "Baidu Wenxin proxy LLM configuration."
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msgstr "Configuration du LLM proxy Baidu Wenxin."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/wenxin.py:62
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msgid "The API key of the Wenxin API."
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msgstr "La clé API de l'API Wenxin."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/wenxin.py:69
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msgid "The API secret key of the Wenxin API."
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msgstr "La clé secrète API de l'API Wenxin."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/claude.py:42
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/claude.py:45
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msgid "Claude Proxy LLM"
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msgstr "LLM Proxy Claude"
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/claude.py:58
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msgid "The base url of the claude API."
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msgstr "L'URL de base de l'API Claude."
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#: ../packages/dbgpt-core/src/dbgpt/model/proxy/llms/claude.py:65
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msgid "The API key of the claude API."
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msgstr "La clé API de l'API Claude."
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#: ../packages/dbgpt-core/src/dbgpt/model/cli.py:312
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msgid "The name of model"
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msgstr "Le nom du modèle"
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#: ../packages/dbgpt-core/src/dbgpt/model/cli.py:319
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msgid "System prompt"
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msgstr "Invite système"
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#: ../packages/dbgpt-core/src/dbgpt/model/cli.py:443
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msgid "The config file to start server"
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msgstr "Le fichier de configuration pour démarrer le serveur"
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#: ../packages/dbgpt-core/src/dbgpt/model/cli.py:451
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msgid ""
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"Run in daemon mode. It will run in the background. If you want to stop it, "
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"use `dbgpt stop` command"
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msgstr ""
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"Exécuter en mode démon. Il fonctionnera en arrière-plan. Si vous souhaitez "
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"l'arrêter, utilisez la commande `dbgpt stop`"
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#: ../packages/dbgpt-core/src/dbgpt/model/cluster/client.py:20
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msgid "Default LLM Client"
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msgstr "Client LLM par défaut"
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#: ../packages/dbgpt-core/src/dbgpt/model/cluster/client.py:23
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msgid "Default LLM client(Connect to your DB-GPT model serving)"
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msgstr ""
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"Client LLM par défaut (Connectez-vous à votre service de modèle DB-GPT)"
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#: ../packages/dbgpt-core/src/dbgpt/model/cluster/client.py:26
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#: ../packages/dbgpt-core/src/dbgpt/model/cluster/client.py:128
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msgid "Auto Convert Message"
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msgstr "Conversion automatique de message"
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#: ../packages/dbgpt-core/src/dbgpt/model/cluster/client.py:32
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#: ../packages/dbgpt-core/src/dbgpt/model/cluster/client.py:134
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msgid ""
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"Whether to auto convert the messages that are not supported by the LLM to a "
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"compatible format"
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msgstr ""
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"Indique s'il faut convertir automatiquement les messages non pris en charge "
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"par le LLM en un format compatible"
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#: ../packages/dbgpt-core/src/dbgpt/model/cluster/client.py:114
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msgid "Remote LLM Client"
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msgstr "Client LLM distant"
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#: ../packages/dbgpt-core/src/dbgpt/model/cluster/client.py:117
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msgid "Remote LLM client(Connect to the remote DB-GPT model serving)"
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msgstr "Client LLM distant (Connexion au service de modèle DB-GPT distant)"
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#: ../packages/dbgpt-core/src/dbgpt/model/cluster/client.py:120
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msgid "Controller Address"
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msgstr "Adresse du contrôleur"
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#: ../packages/dbgpt-core/src/dbgpt/model/cluster/client.py:124
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msgid "http://127.0.0.1:8000"
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msgstr "http://127.0.0.1:8000"
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#: ../packages/dbgpt-core/src/dbgpt/model/cluster/client.py:125
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msgid "Model controller address"
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msgstr "Adresse du contrôleur de modèle"
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#: ../packages/dbgpt-core/src/dbgpt/model/adapter/hf_adapter.py:33
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#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:29
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#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_py_adapter.py:25
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msgid "The path of the model, if you want to deploy a local model."
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msgstr "Le chemin du modèle, si vous souhaitez déployer un modèle local."
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#: ../packages/dbgpt-core/src/dbgpt/model/adapter/hf_adapter.py:41
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#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:64
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#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:37
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#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_py_adapter.py:33
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msgid "Device to run model. If None, the device is automatically determined"
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msgstr "Périphérique pour exécuter le modèle. Si None, le périphérique est automatiquement déterminé"
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#: ../packages/dbgpt-core/src/dbgpt/model/adapter/hf_adapter.py:47
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#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:99
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msgid "Trust remote code or not."
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msgstr "Faire confiance au code distant ou non."
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#: ../packages/dbgpt-core/src/dbgpt/model/adapter/hf_adapter.py:52
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msgid "The quantization parameters."
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msgstr "Les paramètres de quantification."
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#: ../packages/dbgpt-core/src/dbgpt/model/adapter/hf_adapter.py:59
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msgid ""
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"Whether to use low CPU memory usage mode. It can reduce the memory when "
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"loading the model, if you load your model with quantization, it will be True "
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"by default. You must install `accelerate` to make it work."
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msgstr ""
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"Utiliser ou non le mode de faible consommation de mémoire CPU. Cela peut "
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"réduire la mémoire lors du chargement du modèle. Si vous chargez votre "
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"modèle avec quantification, ce mode sera activé par défaut. Vous devez "
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"installer `accelerate` pour que cela fonctionne."
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#: ../packages/dbgpt-core/src/dbgpt/model/adapter/hf_adapter.py:70
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msgid ""
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"The number of gpus you expect to use, if it is empty, use all of them as "
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"much as possible"
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msgstr ""
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"Le nombre de GPU que vous prévoyez d'utiliser. Si ce champ est laissé vide, "
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"tous les GPU disponibles seront utilisés autant que possible."
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#: ../packages/dbgpt-core/src/dbgpt/model/adapter/hf_adapter.py:79
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msgid ""
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"The maximum memory limit of each GPU, only valid in multi-GPU configuration, "
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"eg: 10GiB, 24GiB"
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msgstr ""
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"La limite maximale de mémoire de chaque GPU, valable uniquement en "
|
|
"configuration multi-GPU, par exemple : 10GiB, 24GiB"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/hf_adapter.py:87
|
|
msgid "The dtype of the model, default is None."
|
|
msgstr "Le type de données du modèle, la valeur par défaut est None."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:45
|
|
msgid "Local model file path"
|
|
msgstr "Chemin du fichier de modèle local"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:51
|
|
msgid "Hugging Face repository for model download"
|
|
msgstr "Dépôt Hugging Face pour le téléchargement du modèle"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:56
|
|
msgid "Model file name in the Hugging Face repository"
|
|
msgstr "Nom du fichier de modèle dans le dépôt Hugging Face"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:71
|
|
msgid "Path to the server binary executable"
|
|
msgstr "Chemin vers l'exécutable binaire du serveur"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:75
|
|
msgid "Host address to bind the server"
|
|
msgstr "Adresse hôte pour lier le serveur"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:80
|
|
msgid "Port to bind the server. 0 for random available port"
|
|
msgstr "Port pour lier le serveur. 0 pour un port disponible aléatoire"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:85
|
|
msgid "Sampling temperature for text generation"
|
|
msgstr "Température d'échantillonnage pour la génération de texte"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:89
|
|
msgid "Random seed for reproducibility"
|
|
msgstr "Graine aléatoire pour la reproductibilité"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:92
|
|
msgid "Enable debug mode"
|
|
msgstr "Activer le mode débogage"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:97
|
|
msgid "Model download URL (env: LLAMA_ARG_MODEL_URL)"
|
|
msgstr "URL de téléchargement du modèle (env : LLAMA_ARG_MODEL_URL)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:101
|
|
msgid "Draft model file path"
|
|
msgstr "Chemin du fichier du modèle de brouillon"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:109
|
|
msgid ""
|
|
"Number of threads to use during generation (default: -1) (env: "
|
|
"LLAMA_ARG_THREADS)"
|
|
msgstr ""
|
|
"Nombre de threads à utiliser pendant la génération (par défaut : -1) (env : "
|
|
"LLAMA_ARG_THREADS)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:119
|
|
msgid ""
|
|
"Number of layers to store in VRAM (env: LLAMA_ARG_N_GPU_LAYERS), set "
|
|
"1000000000 to use all layers"
|
|
msgstr ""
|
|
"Nombre de couches à stocker dans la VRAM (env : LLAMA_ARG_N_GPU_LAYERS), "
|
|
"définissez 1000000000 pour utiliser toutes les couches"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:129
|
|
msgid "Logical maximum batch size (default: 2048) (env: LLAMA_ARG_BATCH)"
|
|
msgstr "Taille maximale logique du lot (par défaut : 2048) (env : LLAMA_ARG_BATCH)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:138
|
|
msgid "Physical maximum batch size (default: 512) (env: LLAMA_ARG_UBATCH)"
|
|
msgstr "Taille maximale physique du lot (par défaut : 512) (env : LLAMA_ARG_UBATCH)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:148
|
|
msgid ""
|
|
"Size of the prompt context (default: 4096, 0 = loaded from model) (env: "
|
|
"LLAMA_ARG_CTX_SIZE)"
|
|
msgstr ""
|
|
"Taille du contexte de l'invite (par défaut : 4096, 0 = chargé depuis le "
|
|
"modèle) (env : LLAMA_ARG_CTX_SIZE)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:155
|
|
msgid "Group-attention factor (default: 1)"
|
|
msgstr "Facteur d'attention de groupe (par défaut : 1)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:159
|
|
msgid "Group-attention width (default: 512)"
|
|
msgstr "Largeur d'attention de groupe (par défaut : 512)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:167
|
|
msgid ""
|
|
"Number of tokens to predict (default: -1, -1 = infinity, -2 = until context "
|
|
"filled) (env: LLAMA_ARG_N_PREDICT)"
|
|
msgstr ""
|
|
"Nombre de tokens à prédire (par défaut : -1, -1 = infini, -2 = jusqu'à ce "
|
|
"que le contexte soit rempli) (env : LLAMA_ARG_N_PREDICT)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:176
|
|
msgid "Path to save slot kv cache (default: disabled)"
|
|
msgstr "Chemin pour sauvegarder le cache kv du slot (par défaut : désactivé)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:180
|
|
msgid "Number of slots for KV cache"
|
|
msgstr "Nombre d'emplacements pour le cache KV"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:186
|
|
msgid "Enable continuous batching (a.k.a dynamic batching)"
|
|
msgstr "Activer le traitement par lots continu (alias traitement par lots dynamique)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:193
|
|
msgid ""
|
|
"Restrict to only support embedding use case; use only with dedicated "
|
|
"embedding models (env: LLAMA_ARG_EMBEDDINGS)"
|
|
msgstr "Restreindre pour ne prendre en charge que le cas d'utilisation d'embedding ; "
|
|
"utiliser uniquement avec des modèles d'embedding dédiés (env: "
|
|
"LLAMA_ARG_EMBEDDINGS)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:202
|
|
msgid "Enable reranking endpoint on server (env: LLAMA_ARG_RERANKING)"
|
|
msgstr "Activer le point de terminaison de reranking sur le serveur (env: "
|
|
"LLAMA_ARG_RERANKING)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:210
|
|
msgid ""
|
|
"Enable prometheus compatible metrics endpoint (env: "
|
|
"LLAMA_ARG_ENDPOINT_METRICS)"
|
|
msgstr "Activer le point de terminaison de métriques compatible avec Prometheus "
|
|
"(env: LLAMA_ARG_ENDPOINT_METRICS)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:220
|
|
msgid "Enable slots monitoring endpoint (env: LLAMA_ARG_ENDPOINT_SLOTS)"
|
|
msgstr "Activer le point de terminaison de surveillance des emplacements (env: "
|
|
"LLAMA_ARG_ENDPOINT_SLOTS)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:230
|
|
msgid ""
|
|
"Number of tokens to draft for speculative decoding (default: 16) (env: "
|
|
"LLAMA_ARG_DRAFT_MAX)"
|
|
msgstr "Nombre de tokens à ébaucher pour le décodage spéculatif (par défaut : 16) "
|
|
"(env: LLAMA_ARG_DRAFT_MAX)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:237
|
|
msgid "Same as draft"
|
|
msgstr "Identique à l'ébauche"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:244
|
|
msgid ""
|
|
"Minimum number of draft tokens to use for speculative decoding (default: 5)"
|
|
msgstr ""
|
|
"Nombre minimum de tokens d'ébauche à utiliser pour le décodage spéculatif "
|
|
"(par défaut : 5)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:253
|
|
msgid "API key to use for authentication (env: LLAMA_API_KEY)"
|
|
msgstr "Clé API à utiliser pour l'authentification (env: LLAMA_API_KEY)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:260
|
|
msgid "Path to LoRA adapter (can be repeated to use multiple adapters)"
|
|
msgstr ""
|
|
"Chemin vers l'adaptateur LoRA (peut être répété pour utiliser plusieurs "
|
|
"adaptateurs)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:267
|
|
msgid "Disables context shift on infinite text generation"
|
|
msgstr ""
|
|
"Désactive le décalage de contexte lors de la génération de texte infini"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:271
|
|
msgid "Disable web UI"
|
|
msgstr "Désactiver l'interface web"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_adapter.py:274
|
|
msgid "Server startup timeout in seconds"
|
|
msgstr "Délai d'expiration du démarrage du serveur en secondes"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:105
|
|
msgid ""
|
|
"Directory to download and load the weights, default to the default cache dir "
|
|
"of huggingface."
|
|
msgstr ""
|
|
"Répertoire pour télécharger et charger les poids, par défaut le répertoire "
|
|
"de cache par défaut de huggingface."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:115
|
|
msgid ""
|
|
"The format of the model weights to load.\n"
|
|
"\n"
|
|
"* \"auto\" will try to load the weights in the safetensors format and fall "
|
|
"back to the pytorch bin format if safetensors format is not available.\n"
|
|
"* \"pt\" will load the weights in the pytorch bin format.\n"
|
|
"* \"safetensors\" will load the weights in the safetensors format.\n"
|
|
"* \"npcache\" will load the weights in pytorch format and store a numpy "
|
|
"cache to speed up the loading.\n"
|
|
"* \"dummy\" will initialize the weights with random values, which is mainly "
|
|
"for profiling.\n"
|
|
"* \"tensorizer\" will load the weights using tensorizer from CoreWeave. See "
|
|
"the Tensorize vLLM Model script in the Examples section for more "
|
|
"information.\n"
|
|
"* \"runai_streamer\" will load the Safetensors weights using Run:aiModel "
|
|
"Streamer \n"
|
|
"* \"bitsandbytes\" will load the weights using bitsandbytes quantization.\n"
|
|
msgstr ""
|
|
"Le format des poids du modèle à charger.\n"
|
|
"\n"
|
|
"* \"auto\" tentera de charger les poids au format safetensors et, si ce "
|
|
"format n'est pas disponible, utilisera le format binaire PyTorch.\n"
|
|
"* \"pt\" chargera les poids au format binaire PyTorch.\n"
|
|
"* \"safetensors\" chargera les poids au format safetensors.\n"
|
|
"* \"npcache\" chargera les poids au format PyTorch et stockera un cache "
|
|
"NumPy pour accélérer le chargement.\n"
|
|
"* \"dummy\" initialisera les poids avec des valeurs aléatoires, "
|
|
"principalement à des fins de profilage.\n"
|
|
"* \"tensorizer\" chargera les poids en utilisant le tensorizer de CoreWeave. "
|
|
"Consultez le script Tensorize vLLM Model dans la section Exemples pour plus "
|
|
"d'informations.\n"
|
|
"* \"runai_streamer\" chargera les poids Safetensors en utilisant le "
|
|
"Run:aiModel Streamer.\n"
|
|
"* \"bitsandbytes\" chargera les poids en utilisant la quantification "
|
|
"bitsandbytes.\n"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:152
|
|
msgid ""
|
|
"The format of the model config to load.\n"
|
|
"\n"
|
|
"* \"auto\" will try to load the config in hf format if available else it "
|
|
"will try to load in mistral format "
|
|
msgstr ""
|
|
"Le format de la configuration du modèle à charger.\n"
|
|
"\n"
|
|
"* \"auto\" essaiera de charger la configuration au format hf si disponible, "
|
|
"sinon il essaiera de la charger au format mistral"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:167
|
|
msgid ""
|
|
"Data type for model weights and activations.\n"
|
|
"\n"
|
|
"* \"auto\" will use FP16 precision for FP32 and FP16 models, and BF16 "
|
|
"precision for BF16 models.\n"
|
|
"* \"half\" for FP16. Recommended for AWQ quantization.\n"
|
|
"* \"float16\" is the same as \"half\".\n"
|
|
"* \"bfloat16\" for a balance between precision and range.\n"
|
|
"* \"float\" is shorthand for FP32 precision.\n"
|
|
"* \"float32\" for FP32 precision."
|
|
msgstr ""
|
|
"Type de données pour les poids et les activations du modèle.\n"
|
|
"\n"
|
|
"* \"auto\" utilisera la précision FP16 pour les modèles FP32 et FP16, et la "
|
|
"précision BF16 pour les modèles BF16.\n"
|
|
"* \"half\" pour FP16. Recommandé pour la quantification AWQ.\n"
|
|
"* \"float16\" est identique à \"half\".\n"
|
|
"* \"bfloat16\" pour un équilibre entre précision et plage.\n"
|
|
"* \"float\" est un raccourci pour la précision FP32.\n"
|
|
"* \"float32\" pour la précision FP32."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:183
|
|
msgid ""
|
|
"Data type for kv cache storage. If \"auto\", will use model data type. CUDA "
|
|
"11.8+ supports fp8 (=fp8_e4m3) and fp8_e5m2. ROCm (AMD GPU) supports fp8 "
|
|
"(=fp8_e4m3)"
|
|
msgstr ""
|
|
"Type de données pour le stockage du cache kv. Si \"auto\", le type de "
|
|
"données du modèle sera utilisé. CUDA 11.8+ prend en charge fp8 (=fp8_e4m3) "
|
|
"et fp8_e5m2. ROCm (AMD GPU) prend en charge fp8 (=fp8_e4m3)."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:193
|
|
msgid "Random seed for operations."
|
|
msgstr "Graine aléatoire pour les opérations."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:200
|
|
msgid ""
|
|
"Model context length. If unspecified, will be automatically derived from the "
|
|
"model config."
|
|
msgstr ""
|
|
"Longueur du contexte du modèle. Si non spécifiée, elle sera automatiquement "
|
|
"dérivée de la configuration du modèle."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:209
|
|
msgid ""
|
|
"Backend to use for distributed model workers, either \"ray\" or \"mp\" "
|
|
"(multiprocessing). If the product of pipeline_parallel_size and "
|
|
"tensor_parallel_size is less than or equal to the number of GPUs available, "
|
|
"\"mp\" will be used to keep processing on a single host. Otherwise, this "
|
|
"will default to \"ray\" if Ray is installed and fail otherwise. Note that "
|
|
"tpu only supports Ray for distributed inference."
|
|
msgstr ""
|
|
"Backend à utiliser pour les travailleurs de modèle distribué, soit \"ray\" "
|
|
"soit \"mp\" (multiprocessing). Si le produit de pipeline_parallel_size et "
|
|
"tensor_parallel_size est inférieur ou égal au nombre de GPU disponibles, "
|
|
"\"mp\" sera utilisé pour conserver le traitement sur un seul hôte. Sinon, "
|
|
"cela passera par défaut à \"ray\" si Ray est installé et échouera sinon. "
|
|
"Notez que le TPU ne prend en charge que Ray pour l'inférence distribuée."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:223
|
|
msgid "Number of pipeline stages."
|
|
msgstr "Nombre d'étapes du pipeline."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:229
|
|
msgid "Number of tensor parallel replicas."
|
|
msgstr "Nombre de répliques parallèles de tenseurs."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:236
|
|
msgid ""
|
|
"Load model sequentially in multiple batches, to avoid RAM OOM when using "
|
|
"tensor parallel and large models."
|
|
msgstr ""
|
|
"Charger le modèle séquentiellement en plusieurs lots, pour éviter un "
|
|
"dépassement de mémoire RAM lors de l'utilisation du parallélisme tensoriel "
|
|
"et de grands modèles."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:245
|
|
msgid ""
|
|
"Token block size for contiguous chunks of tokens. This is ignored on neuron "
|
|
"devices and set to ``--max-model-len``. On CUDA devices, only block sizes up "
|
|
"to 32 are supported. On HPU devices, block size defaults to 128."
|
|
msgstr ""
|
|
"Taille de bloc de Token pour des segments contigus de Tokens. Ceci est "
|
|
"ignoré sur les appareils neuronaux et défini à ``--max-model-len``. Sur les "
|
|
"appareils CUDA, seules les tailles de bloc jusqu'à 32 sont supportées. Sur "
|
|
"les appareils HPU, la taille de bloc par défaut est de 128."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:256
|
|
msgid "Enables automatic prefix caching. "
|
|
msgstr "Active la mise en cache automatique des préfixes."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:262
|
|
msgid "CPU swap space size (GiB) per GPU."
|
|
msgstr "Taille de l'espace d'échange CPU (GiB) par GPU."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:269
|
|
msgid ""
|
|
"The space in GiB to offload to CPU, per GPU. Default is 0, which means no "
|
|
"offloading. Intuitively, this argument can be seen as a virtual way to "
|
|
"increase the GPU memory size. For example, if you have one 24 GB GPU and set "
|
|
"this to 10, virtually you can think of it as a 34 GB GPU. Then you can load "
|
|
"a 13B model with BF16 weight, which requires at least 26GB GPU memory. Note "
|
|
"that this requires fast CPU-GPU interconnect, as part of the model is loaded "
|
|
"from CPU memory to GPU memory on the fly in each model forward pass."
|
|
msgstr ""
|
|
"L'espace en GiB à transférer vers le CPU, par GPU. La valeur par défaut est "
|
|
"0, ce qui signifie qu'aucun transfert n'est effectué. De manière intuitive, "
|
|
"cet argument peut être considéré comme un moyen virtuel d'augmenter la "
|
|
"taille de la mémoire GPU. Par exemple, si vous avez un GPU de 24 Go et que "
|
|
"vous le paramétrez à 10, vous pouvez considérer virtuellement qu'il s'agit "
|
|
"d'un GPU de 34 Go. Vous pouvez alors charger un modèle de 13 milliards de "
|
|
"paramètres avec des poids en BF16, qui nécessite au moins 26 Go de mémoire "
|
|
"GPU. Notez que cela nécessite une interconnexion rapide entre le CPU et le "
|
|
"GPU, car une partie du modèle est chargée de la mémoire du CPU vers la "
|
|
"mémoire du GPU à chaque passage avant du modèle."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:286
|
|
#, python-format
|
|
msgid ""
|
|
"The fraction of GPU memory to be used for the model executor, which can "
|
|
"range from 0 to 1. For example, a value of 0.5 would imply 50%% GPU memory "
|
|
"utilization. If unspecified, will use the default value of 0.9. This is a "
|
|
"per-instance limit, and only applies to the current vLLM instance.It does "
|
|
"not matter if you have another vLLM instance running on the same GPU. For "
|
|
"example, if you have two vLLM instances running on the same GPU, you can set "
|
|
"the GPU memory utilization to 0.5 for each instance."
|
|
msgstr ""
|
|
"La fraction de mémoire GPU à utiliser pour l'exécuteur de modèle, qui peut "
|
|
"varier de 0 à 1. Par exemple, une valeur de 0.5 impliquerait une utilisation "
|
|
"de 50%% de la mémoire GPU. Si non spécifié, la valeur par défaut de 0.9 sera "
|
|
"utilisée. Il s'agit d'une limite par instance et ne s'applique qu'à "
|
|
"l'instance vLLM actuelle. Peu importe si vous avez une autre instance vLLM "
|
|
"en cours d'exécution sur le même GPU. Par exemple, si vous avez deux "
|
|
"instances vLLM en cours d'exécution sur le même GPU, vous pouvez définir "
|
|
"l'utilisation de la mémoire GPU à 0.5 pour chaque instance."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:301
|
|
msgid "Maximum number of batched tokens per iteration."
|
|
msgstr "Nombre maximum de tokens groupés par itération."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:307
|
|
msgid "Maximum number of sequences per iteration."
|
|
msgstr "Nombre maximum de séquences par itération."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:314
|
|
msgid ""
|
|
"Max number of log probs to return logprobs is specified in SamplingParams."
|
|
msgstr ""
|
|
"Nombre maximum de log probs à retourner, logprobs est spécifié dans "
|
|
"SamplingParams."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:323
|
|
msgid ""
|
|
"The specific model version to use. It can be a branch name, a tag name, or a "
|
|
"commit id. If unspecified, will use the default version."
|
|
msgstr ""
|
|
"La version spécifique du modèle à utiliser. Il peut s'agir d'un nom de "
|
|
"branche, d'un nom de tag ou d'un identifiant de commit. Si non spécifié, la "
|
|
"version par défaut sera utilisée."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:333
|
|
msgid ""
|
|
"The specific revision to use for the model code on Hugging Face Hub. It can "
|
|
"be a branch name, a tag name, or a commit id. If unspecified, will use the "
|
|
"default version."
|
|
msgstr ""
|
|
"La révision spécifique à utiliser pour le code du modèle sur Hugging Face "
|
|
"Hub. Il peut s'agir d'un nom de branche, d'un nom de tag ou d'un identifiant "
|
|
"de commit. Si non spécifié, la version par défaut sera utilisée."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:343
|
|
msgid ""
|
|
"Revision of the huggingface tokenizer to use. It can be a branch name, a tag "
|
|
"name, or a commit id. If unspecified, will use the default version."
|
|
msgstr ""
|
|
"Révision du tokenizer huggingface à utiliser. Il peut s'agir d'un nom de "
|
|
"branche, d'un nom de tag ou d'un identifiant de commit. Si non spécifié, la "
|
|
"version par défaut sera utilisée."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:353
|
|
msgid ""
|
|
"The tokenizer mode.\n"
|
|
"\n"
|
|
"* \"auto\" will use the fast tokenizer if available.\n"
|
|
"* \"slow\" will always use the slow tokenizer. \n"
|
|
"* \"mistral\" will always use the `mistral_common` tokenizer."
|
|
msgstr ""
|
|
"Le mode du tokenizer.\n"
|
|
"\n"
|
|
"* \"auto\" utilisera le tokenizer rapide si disponible.\n"
|
|
"* \"slow\" utilisera toujours le tokenizer lent. \n"
|
|
"* \"mistral\" utilisera toujours le tokenizer `mistral_common`."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:365
|
|
msgid ""
|
|
"Method used to quantize the weights. If None, we first check the "
|
|
"`quantization_config` attribute in the model config file. If that is None, "
|
|
"we assume the model weights are not quantized and use `dtype` to determine "
|
|
"the data type of the weights."
|
|
msgstr ""
|
|
"Méthode utilisée pour quantifier les poids. Si None, nous vérifions d'abord "
|
|
"l'attribut `quantization_config` dans le fichier de configuration du modèle. "
|
|
"Si celui-ci est None, nous supposons que les poids du modèle ne sont pas "
|
|
"quantifiés et utilisons `dtype` pour déterminer le type de données des poids."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:403
|
|
msgid ""
|
|
"Maximum sequence length covered by CUDA graphs. When a sequence has context "
|
|
"length larger than this, we fall back to eager mode. Additionally for "
|
|
"encoder-decoder models, if the sequence length of the encoder input is "
|
|
"larger than this, we fall back to the eager mode."
|
|
msgstr ""
|
|
"Longueur maximale de séquence couverte par les graphes CUDA. Lorsqu'une "
|
|
"séquence a une longueur de contexte supérieure à celle-ci, nous revenons au "
|
|
"mode eager. De plus, pour les modèles encodeur-décodeur, si la longueur de "
|
|
"séquence de l'entrée de l'encodeur est supérieure à celle-ci, nous revenons "
|
|
"au mode eager."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:414
|
|
msgid "The worker class to use for distributed execution."
|
|
msgstr "La classe de worker à utiliser pour l'exécution distribuée."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/vllm_adapter.py:418
|
|
msgid "Extra parameters, it will be passed to the vllm engine."
|
|
msgstr "Paramètres supplémentaires, ils seront passés au moteur vllm."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/embed_metadata.py:27
|
|
msgid ""
|
|
"The embedding model are trained by BAAI, it support more than 100 working "
|
|
"languages."
|
|
msgstr ""
|
|
"Le modèle d'embedding est entraîné par BAAI, il prend en charge plus de 100 "
|
|
"langues de travail."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/embed_metadata.py:36
|
|
msgid "The embedding model are trained by BAAI, it support Chinese."
|
|
msgstr "Le modèle d'embedding est entraîné par BAAI, il prend en charge le chinois."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/embed_metadata.py:44
|
|
msgid "The embedding model are trained by BAAI, it support English."
|
|
msgstr "Le modèle d'embedding est entraîné par BAAI, il prend en charge l'anglais."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/embed_metadata.py:54
|
|
msgid ""
|
|
"The embedding model are trained by Jina AI, it support multiple languages. "
|
|
"And it has 0.57B parameters."
|
|
msgstr ""
|
|
"Le modèle d'embedding est entraîné par Jina AI, il prend en charge plusieurs "
|
|
"langues. Et il a 0,57 milliard de paramètres."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/embed_metadata.py:65
|
|
msgid "The reranker model are trained by BAAI, it support multiple languages."
|
|
msgstr "Le modèle de reranking est entraîné par BAAI, il prend en charge plusieurs langues."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/embed_metadata.py:73
|
|
msgid "The reranker model are trained by BAAI, it support Chinese and English."
|
|
msgstr "Le modèle de reranking est entraîné par BAAI, il prend en charge le chinois et l'anglais."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/embed_metadata.py:85
|
|
msgid ""
|
|
"The reranker model are trained by Jina AI, it support multiple languages."
|
|
msgstr ""
|
|
"Le modèle de reranking est entraîné par Jina AI, il prend en charge plusieurs langues."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_py_adapter.py:39
|
|
msgid "Random seed for llama-cpp models. -1 for random"
|
|
msgstr "Graine aléatoire pour les modèles llama-cpp. -1 pour aléatoire"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_py_adapter.py:45
|
|
msgid ""
|
|
"Number of threads to use. If None, the number of threads is automatically "
|
|
"determined"
|
|
msgstr ""
|
|
"Nombre de threads à utiliser. Si None, le nombre de threads est déterminé "
|
|
"automatiquement"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_py_adapter.py:54
|
|
msgid ""
|
|
"Maximum number of prompt tokens to batch together when calling llama_eval"
|
|
msgstr ""
|
|
"Nombre maximum de tokens de prompt à regrouper lors de l'appel à llama_eval"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_py_adapter.py:63
|
|
msgid ""
|
|
"Number of layers to offload to the GPU, Set this to 1000000000 to offload "
|
|
"all layers to the GPU."
|
|
msgstr ""
|
|
"Nombre de couches à transférer sur le GPU. Réglez ce paramètre à 1000000000 "
|
|
"pour transférer toutes les couches sur le GPU."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_py_adapter.py:70
|
|
msgid "Grouped-query attention. Must be 8 for llama-2 70b."
|
|
msgstr "Attention par requête groupée. Doit être 8 pour llama-2 70b."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_py_adapter.py:73
|
|
msgid "5e-6 is a good value for llama-2 models."
|
|
msgstr "5e-6 est une bonne valeur pour les modèles llama-2."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_py_adapter.py:79
|
|
msgid ""
|
|
"Maximum cache capacity. Examples: 2000MiB, 2GiB. When provided without "
|
|
"units, bytes will be assumed. "
|
|
msgstr ""
|
|
"Capacité maximale du cache. Exemples : 2000MiB, 2GiB. Lorsqu'il est fourni "
|
|
"sans unités, les octets seront supposés."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/adapter/llama_cpp_py_adapter.py:88
|
|
msgid ""
|
|
"If a GPU is available, it will be preferred by default, unless "
|
|
"prefer_cpu=False is configured."
|
|
msgstr ""
|
|
"Si un GPU est disponible, il sera préféré par défaut, sauf si "
|
|
"prefer_cpu=False est configuré."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:96
|
|
msgid "Database configuration for model registry"
|
|
msgstr "Configuration de la base de données pour le registre des modèles"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:108
|
|
msgid "Model registry configuration. If None, use embedded registry"
|
|
msgstr ""
|
|
"Configuration du registre des modèles. Si None, utilisez le registre intégré"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:114
|
|
msgid "The interval for checking heartbeats (seconds)"
|
|
msgstr "L'intervalle de vérification des battements de cœur (secondes)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:120
|
|
msgid ""
|
|
"The timeout for checking heartbeats (seconds), it will be set unhealthy if "
|
|
"the worker is not responding in this time"
|
|
msgstr ""
|
|
"Le délai d'attente pour la vérification des battements de cœur (secondes). Il sera marqué comme non sain si le travailleur ne répond pas dans ce délai."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:130
|
|
msgid "Model API server deploy port"
|
|
msgstr "Port de déploiement du serveur API de modèle"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:134
|
|
msgid "The Model controller address to connect"
|
|
msgstr "L'adresse du contrôleur de modèle à connecter"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:139
|
|
msgid "Optional list of comma separated API keys"
|
|
msgstr "Liste facultative de clés API séparées par des virgules"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:142
|
|
msgid "Embedding batch size"
|
|
msgstr "Taille du lot d'incorporation"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:145
|
|
msgid "Ignore exceeds stop words error"
|
|
msgstr "Ignorer l'erreur de dépassement des mots de fin"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:153
|
|
msgid "Worker type"
|
|
msgstr "Type de travailleur"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:158
|
|
msgid "Model worker class, dbgpt.model.cluster.DefaultModelWorker"
|
|
msgstr "Classe de travailleur de modèle, dbgpt.model.cluster.DefaultModelWorker"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:167
|
|
msgid "Standalone mode. If True, embedded Run ModelController"
|
|
msgstr "Mode autonome. Si True, exécute le Contrôleur de modèle intégré"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:171
|
|
msgid "Register current worker to model controller"
|
|
msgstr "Inscrire le travailleur actuel au contrôleur de modèle"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:190
|
|
msgid "The interval for sending heartbeats (seconds)"
|
|
msgstr "L'intervalle d'envoi des signaux de vie (secondes)"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:202
|
|
msgid "Model worker configuration"
|
|
msgstr "Configuration du travailleur de modèle"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:205
|
|
msgid "Model API"
|
|
msgstr "API de modèle"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:209
|
|
msgid "Model controller"
|
|
msgstr "Contrôleur de modèle"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:220
|
|
msgid ""
|
|
"Default LLM model name, used to specify which model to use when you have "
|
|
"multiple LLMs"
|
|
msgstr ""
|
|
"Nom du modèle LLM par défaut, utilisé pour spécifier quel modèle utiliser "
|
|
"lorsque vous avez plusieurs LLMs"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:229
|
|
msgid ""
|
|
"Default embedding model name, used to specify which model to use when you "
|
|
"have multiple embedding models"
|
|
msgstr ""
|
|
"Nom du modèle d'embedding par défaut, utilisé pour spécifier quel modèle "
|
|
"utiliser lorsque vous avez plusieurs modèles d'embedding"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:238
|
|
msgid ""
|
|
"Default reranker model name, used to specify which model to use when you "
|
|
"have multiple reranker models"
|
|
msgstr ""
|
|
"Nom du modèle de reranker par défaut, utilisé pour spécifier quel modèle "
|
|
"utiliser lorsque vous avez plusieurs modèles de reranker"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:247
|
|
msgid ""
|
|
"LLM model deploy configuration. If you deploy in cluster mode, you just "
|
|
"deploy one model."
|
|
msgstr ""
|
|
"Configuration de déploiement du modèle LLM. Si vous déployez en mode cluster, vous ne déployez qu'un seul modèle."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:256
|
|
msgid ""
|
|
"Embedding model deploy configuration. If you deploy in cluster mode, you "
|
|
"just deploy one model."
|
|
msgstr ""
|
|
"Configuration de déploiement du modèle d'embedding. Si vous déployez en mode cluster, vous ne déployez qu'un seul modèle."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/parameter.py:265
|
|
msgid ""
|
|
"Reranker model deploy configuration. If you deploy in cluster mode, you just "
|
|
"deploy one model."
|
|
msgstr ""
|
|
"Configuration de déploiement du modèle de reranker. Si vous déployez en mode cluster, vous ne déployez qu'un seul modèle."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/utils/chatgpt_utils.py:140
|
|
msgid "OpenAI Streaming Output Operator"
|
|
msgstr "Opérateur de sortie en streaming OpenAI"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/utils/chatgpt_utils.py:144
|
|
msgid "The OpenAI streaming LLM operator."
|
|
msgstr "L'opérateur LLM en streaming OpenAI."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/utils/chatgpt_utils.py:148
|
|
msgid "Upstream Model Output"
|
|
msgstr "Sortie du modèle en amont"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/utils/chatgpt_utils.py:152
|
|
msgid "The model output of upstream."
|
|
msgstr "La sortie du modèle en amont."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/utils/chatgpt_utils.py:157
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/operators/llm_operator.py:97
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/operators/llm_operator.py:152
|
|
msgid "Model Output"
|
|
msgstr "Sortie du modèle"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/utils/chatgpt_utils.py:162
|
|
msgid "The model output after transformed to openai stream format."
|
|
msgstr "La sortie du modèle après transformation au format de flux OpenAI."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/operators/llm_operator.py:73
|
|
msgid "LLM Operator"
|
|
msgstr "Opérateur LLM"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/operators/llm_operator.py:76
|
|
msgid "The LLM operator."
|
|
msgstr "L'opérateur LLM."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/operators/llm_operator.py:79
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/operators/llm_operator.py:134
|
|
msgid "LLM Client"
|
|
msgstr "Client LLM"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/operators/llm_operator.py:84
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/operators/llm_operator.py:139
|
|
msgid "The LLM Client."
|
|
msgstr "Le client LLM."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/operators/llm_operator.py:89
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/operators/llm_operator.py:144
|
|
msgid "Model Request"
|
|
msgstr "Requête du modèle"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/operators/llm_operator.py:92
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/operators/llm_operator.py:147
|
|
msgid "The model request."
|
|
msgstr "La requête du modèle."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/operators/llm_operator.py:100
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/operators/llm_operator.py:155
|
|
msgid "The model output."
|
|
msgstr "La sortie du modèle."
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/operators/llm_operator.py:127
|
|
msgid "Streaming LLM Operator"
|
|
msgstr "Opérateur LLM en streaming"
|
|
|
|
#: ../packages/dbgpt-core/src/dbgpt/model/operators/llm_operator.py:131
|
|
msgid "The streaming LLM operator."
|
|
msgstr "L'opérateur LLM en streaming." |