MODEL TRAINING
    41.
    发明申请

    公开(公告)号:US20220198153A1

    公开(公告)日:2022-06-23

    申请号:US17694034

    申请日:2022-03-14

    Abstract: A model training method, a model training platform, an electronic device and a storage medium are provided, which can be used in the field of artificial intelligence, particularly the fields of natural language processing and deep learning. The model training method includes: receiving an input; determining, based on the input, a user-oriented prefabricated function; determining, based on the input, a model training function; determining, based on the input, a pre-trained model; determining, based on the input, a network structure associated with the pre-trained model so as to support use of the pre-trained model; training, based on the input, the model by using the prefabricated function, the model training function, and the pre-trained model; and providing an output associated with a trained model.

    METHOD OF CONSTRUCTING NETWORK MODEL FOR DEEP LEARNING, DEVICE, AND STORAGE MEDIUM

    公开(公告)号:US20220058490A1

    公开(公告)日:2022-02-24

    申请号:US17519815

    申请日:2021-11-05

    Abstract: A method and apparatus of constructing a network model for deep learning, a device, and a storage medium, which relate to artificial intelligence, and in particular to a field of deep learning. The method of constructing the network model for deep learning includes: determining an execution mode for executing codes, based on a mode parameter; executing the codes by using a first component, which is executable in a first execution mode, through a syntax element in the codes, in response to determining that the execution mode is the first execution mode; and executing the codes by using a second component, which is executable in a second execution mode, through the syntax element, in response to determining that the execution mode is the second execution mode; wherein the first component and the second component have the same component interface, and the syntax element corresponds to the component interface.

    OPERATOR PROCESSING METHOD OF DEEP LEARNING FRAMEWORK, DEVICE AND STORAGE MEDIUM

    公开(公告)号:US20250005446A1

    公开(公告)日:2025-01-02

    申请号:US18547090

    申请日:2022-11-02

    Abstract: An operator processing method of a deep learning framework an electronic device, and a storage medium are provided, which relate to a field of computer technology, especially in a field of artificial intelligence technology such as deep learning. The specific implementation scheme includes: acquiring an operator to be processed, where the operator to be processed includes a template parameter independent of the deep learning framework and an operator kernel function; parsing, in response to receiving an input information for the operator to be processed, the template parameter by using the input information to obtain a plurality of complete template parameters related to the deep learning framework; and processing the operator kernel function according to the plurality of complete template parameters, to obtain an available operator for the deep learning framework.

    DIALOGUE MODEL TRAINING METHOD
    45.
    发明申请

    公开(公告)号:US20240412002A1

    公开(公告)日:2024-12-12

    申请号:US18747641

    申请日:2024-06-19

    Abstract: A method is provided. The method includes: obtaining a first sample dataset; inputting at least one first question text corresponding to at least one piece of first sample data into a dialog model separately to obtain at least one first answer prediction result; inputting each second question text into the dialog model to obtain a second answer prediction result output by the dialog model; inputting the second answer prediction result into a reward model to obtain a score of the second answer prediction result output by the reward model; determining a comprehensive loss based on the at least one first answer prediction result, a first answer text of each of the at least one piece of first sample data, and a score corresponding to each of at least one piece of second sample data; and adjusting at least one parameter of the dialog model based on the comprehensive loss.

    METHOD OF PROCESSING DATA, ELECTRONIC DEVICE, AND MEDIUM

    公开(公告)号:US20230086145A1

    公开(公告)日:2023-03-23

    申请号:US17936761

    申请日:2022-09-29

    Abstract: A method of processing data, a device, and a medium are provided, which relate to a field of an artificial intelligence technology, in particular to fields of computer vision, natural language technology, speech technology, deep learning and knowledge graph. The method of processing data includes: generating a video feature, a question feature and an answer feature based on acquired video data, acquired question data and acquired candidate answer data; determining a link relationship between the video feature, the question feature and the answer feature; and determining a matching result for the video data, the question data and the candidate answer data based on the link relationship.

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