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refactor: i18n

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wxg0103 2025-03-05 13:58:27 +08:00
parent e36f6e08f7
commit 83d51ea866
2 changed files with 6 additions and 6 deletions
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6
apps/locales/zh_CN/LC_MESSAGES/django.po
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@ -4087,7 +4087,7 @@ msgstr "输出最大Token数"
#: .\apps\setting\models_provider\impl\zhipu_model_provider\credential\image.py:24
#: .\apps\setting\models_provider\impl\zhipu_model_provider\credential\llm.py:31
msgid "Specify the maximum number of tokens that the model can generate"
msgstr "指定模型可以生成的最大令牌数"
msgstr "指定模型可以生成的最大 tokens 数"
#: .\apps\setting\models_provider\impl\aliyun_bai_lian_model_provider\credential\image.py:50
#: .\apps\setting\models_provider\impl\aliyun_bai_lian_model_provider\credential\llm.py:44
@ -4423,7 +4423,7 @@ msgid ""
"retrieval-augmented generation (RAG). At launch, the model is optimized for "
"English, but other languages are supported."
msgstr ""
"Amazon Titan Text Express 的上下文长度长达 8000 个令牌，因而非常适合各种高级"
"Amazon Titan Text Express 的上下文长度长达 8000 个 tokens，因而非常适合各种高级"
"常规语言任务，例如开放式文本生成和对话式聊天，以及检索增强生成（RAG）中的支"
"持。在发布时，该模型针对英语进行了优化，但也支持其他语言。"
@ -4686,7 +4686,7 @@ msgstr "Phi-3 Mini是Microsoft的3.8B参数，轻量级，最先进的开放模
#: .\apps\setting\models_provider\impl\ollama_model_provider\ollama_model_provider.py:167
msgid ""
"A high-performance open embedding model with a large token context window."
msgstr "一个具有大令牌上下文窗口的高性能开放嵌入模型。"
msgstr "一个具有大 tokens上下文窗口的高性能开放嵌入模型。"
#: .\apps\setting\models_provider\impl\openai_model_provider\credential\tti.py:15
msgid ""

6
apps/locales/zh_Hant/LC_MESSAGES/django.po
View File

@ -4099,7 +4099,7 @@ msgstr "輸出最大Token數"
#: .\apps\setting\models_provider\impl\zhipu_model_provider\credential\image.py:24
#: .\apps\setting\models_provider\impl\zhipu_model_provider\credential\llm.py:31
msgid "Specify the maximum number of tokens that the model can generate"
msgstr "指定模型可以生成的最大令牌數"
msgstr "指定模型可以生成的最大 tokens"
#: .\apps\setting\models_provider\impl\aliyun_bai_lian_model_provider\credential\image.py:50
#: .\apps\setting\models_provider\impl\aliyun_bai_lian_model_provider\credential\llm.py:44
@ -4435,7 +4435,7 @@ msgid ""
"retrieval-augmented generation (RAG). At launch, the model is optimized for "
"English, but other languages are supported."
msgstr ""
"Amazon Titan Text Express 的上下文長度長達 8000 個令牌，因而非常適合各種高級"
"Amazon Titan Text Express 的上下文長度長達 8000 個 tokens，因而非常適合各種高級"
"常規語言任務，例如開放式文本生成和對話式聊天，以及檢索增強生成（RAG）中的支"
"持。在發佈時，該模型針對英語進行了優化，但也支持其他語言。"
@ -4698,7 +4698,7 @@ msgstr "Phi-3 Mini是Microsoft的3.8B參數，輕量級，最先進的開放模
#: .\apps\setting\models_provider\impl\ollama_model_provider\ollama_model_provider.py:167
msgid ""
"A high-performance open embedding model with a large token context window."
msgstr "一個具有大令牌上下文窗口的高性能開放嵌入模型。"
msgstr "一個具有大 tokens 上下文窗口的高性能開放嵌入模型。"
#: .\apps\setting\models_provider\impl\openai_model_provider\credential\tti.py:15
msgid ""