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ChatGPT解決翻譯中英文數(shù)量不對應(yīng)的prompt

2023-06-18 08:35 作者:28258797054_bili  | 我要投稿

{{#system~}} You are a helpful assistant, I have two arrays of strings: one in Source and one in Translated. The Translated array is a translation of the Source array, but the number of strings in each array is not the same. I need to correct this so that each string in the Source array corresponds to a string in the Translated array. Follow these steps: Step 1: Iterate over each string in the Translated translation array. For each Translated string, find all corresponding subset strings in the Source array. Count how many Source strings correspond to each Translated string. Step 2: Split each Translated string according to the number of corresponding English strings. Do not add or duplicate new content. Only response a JSON array with the following format: [ { "translated": "Translated item 1", "sources": ["Source Item1", "Source Item2"], "count": 2, "fragments": ["Translated fragment 1", "Translated fragment 2"] } ] {{~/system}} {{#user~}} Source array: [ "JOHN EWALD: Hello, and welcome to Introduction", "to Large Language Models.", "My name is John Ewald, and I'm a training developer here", "at Google Cloud.", "In this course, you learn to define large language", "models, or LLMs, describe LLM use cases,", "explain prompt tuning, and describe Google's Gen AI", "development tools.", "Large language models, or LLMs, are a subset of deep learning.", "To find out more about deep learning,", "see our Introduction to Generative AI course video." ] Translated array: [ "約翰·尤瓦爾德:你好,歡迎來到大型語言模型介紹。", "我叫約翰·尤瓦爾德,在谷歌云這里是一名培訓(xùn)開發(fā)者。", "在這門課程中,您將學(xué)習(xí)定義大型語言模型(LLM),描述LLM的用例,", "解釋提示調(diào)優(yōu),以及描述谷歌的Gen AI開發(fā)工具。", "大型語言模型(LLM)是深度學(xué)習(xí)的一個子集。", "要了解更多關(guān)于深度學(xué)習(xí)的信息,請觀看我們的生成性AI課程視頻。" ] Here is the JSON string: {{~/user}}

ChatGPT解決翻譯中英文數(shù)量不對應(yīng)的prompt的評論 (共 條)

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