METHOD OF GENERATING CODE BASED ON LARGE MODEL, ELECTRONIC DEVICE, AND STORAGE MEDIUM

    公开(公告)号:US20250094139A1

    公开(公告)日:2025-03-20

    申请号:US18965152

    申请日:2024-12-02

    Abstract: A method of generating a code based on a large model, an electronic device and a storage medium are provided, which relate to the field of artificial intelligence technology, in particular to the fields of deep learning technology and large model technology. The method includes: acquiring a first descriptive text input by a user, where the first descriptive text is configured to characterize a code requirement; searching for a positive code and a negative code matching the first descriptive text, where each of the positive code and the negative code is determined based on a preference operation of the user for a historical code output by the large model; generating a second descriptive text according to the first descriptive text, the positive code, and the negative code; and inputting the second descriptive text into the large model to output a target code matching the code requirement.

    WORD MINING METHOD AND APPARATUS, ELECTRONIC DEVICE AND READABLE STORAGE MEDIUM

    公开(公告)号:US20230052623A1

    公开(公告)日:2023-02-16

    申请号:US17812120

    申请日:2022-07-12

    Abstract: The present disclosure provides a word mining method and apparatus, an electronic device and a readable storage medium, and relates to the field of artificial intelligence technologies, such as natural language processing technologies, deep learning technologies, cloud service technologies, or the like. The word mining method includes: acquiring search data; taking first identification information, a search sentence and second identification information in the search data as nodes, and taking a relationship between the first identification information and the search sentence, a relationship between the first identification information and the second identification information and a relationship between the search sentence and the second identification information as sides to construct a behavior graph; obtaining a label vector of each search sentence in the behavior graph according to a search sentence with a preset label in the behavior graph; determining a target search sentence in the behavior graph according to the label vector; and extracting a target word from the target search sentence, and taking the target word as a word mining result of the search data.

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