AI MODEL TRAINING METHOD AND APPARATUS, AND COMPUTING DEVICE AND STORAGE MEDIUM
This application provides a method and an apparatus for training an AI model, a computing device, and a storage medium, and relates to the field of artificial intelligence technologies. The method is applied to an AI platform, the AI platform is associated with a computing resource pool, the computi...
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creator | HUANG, Zhesi DAI, Zonghong YANG, Bingbing WU, Renke LI, Yi ZHU, Jiangcheng ZHONG, Jinghua BAI, Xiaolong |
description | This application provides a method and an apparatus for training an AI model, a computing device, and a storage medium, and relates to the field of artificial intelligence technologies. The method is applied to an AI platform, the AI platform is associated with a computing resource pool, the computing resource pool includes a compute node used for model training, and the method includes: providing a training configuration interface for a user, where the training configuration interface includes a plurality of training modes for the user to select, and each training mode represents an allocation policy for compute nodes required for training an initial AI model; generating at least one training task based on a selection of the user on the training configuration interface; and performing the at least one training task to train the initial AI model, to obtain an AI model, where the obtained AI model is provided for the user to download or use. According to this application, distributed training can be performed more flexibly. |
format | Patent |
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The method is applied to an AI platform, the AI platform is associated with a computing resource pool, the computing resource pool includes a compute node used for model training, and the method includes: providing a training configuration interface for a user, where the training configuration interface includes a plurality of training modes for the user to select, and each training mode represents an allocation policy for compute nodes required for training an initial AI model; generating at least one training task based on a selection of the user on the training configuration interface; and performing the at least one training task to train the initial AI model, to obtain an AI model, where the obtained AI model is provided for the user to download or use. 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The method is applied to an AI platform, the AI platform is associated with a computing resource pool, the computing resource pool includes a compute node used for model training, and the method includes: providing a training configuration interface for a user, where the training configuration interface includes a plurality of training modes for the user to select, and each training mode represents an allocation policy for compute nodes required for training an initial AI model; generating at least one training task based on a selection of the user on the training configuration interface; and performing the at least one training task to train the initial AI model, to obtain an AI model, where the obtained AI model is provided for the user to download or use. According to this application, distributed training can be performed more flexibly.</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZPB39FTw9Xdx9VEICXL09PP0c1fwdQ3x8HdRcPQD4oAAxyDHkNBgHTDX2d83IDQEpMbFNczT2RUsGBziH-To7grU5uIZ6svDwJqWmFOcyguluRkU3FxDnD10Uwvy41OLCxKTU_NSS-JdA0yMDCwtzY0cTYyJUAIAp4gt8A</recordid><startdate>20240306</startdate><enddate>20240306</enddate><creator>HUANG, Zhesi</creator><creator>DAI, Zonghong</creator><creator>YANG, Bingbing</creator><creator>WU, Renke</creator><creator>LI, Yi</creator><creator>ZHU, Jiangcheng</creator><creator>ZHONG, Jinghua</creator><creator>BAI, Xiaolong</creator><scope>EVB</scope></search><sort><creationdate>20240306</creationdate><title>AI MODEL TRAINING METHOD AND APPARATUS, AND COMPUTING DEVICE AND STORAGE MEDIUM</title><author>HUANG, Zhesi ; DAI, Zonghong ; YANG, Bingbing ; WU, Renke ; LI, Yi ; ZHU, Jiangcheng ; ZHONG, Jinghua ; BAI, Xiaolong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_EP4209972A43</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng ; fre ; ger</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>HUANG, Zhesi</creatorcontrib><creatorcontrib>DAI, Zonghong</creatorcontrib><creatorcontrib>YANG, Bingbing</creatorcontrib><creatorcontrib>WU, Renke</creatorcontrib><creatorcontrib>LI, Yi</creatorcontrib><creatorcontrib>ZHU, Jiangcheng</creatorcontrib><creatorcontrib>ZHONG, Jinghua</creatorcontrib><creatorcontrib>BAI, Xiaolong</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>HUANG, Zhesi</au><au>DAI, Zonghong</au><au>YANG, Bingbing</au><au>WU, Renke</au><au>LI, Yi</au><au>ZHU, Jiangcheng</au><au>ZHONG, Jinghua</au><au>BAI, Xiaolong</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>AI MODEL TRAINING METHOD AND APPARATUS, AND COMPUTING DEVICE AND STORAGE MEDIUM</title><date>2024-03-06</date><risdate>2024</risdate><abstract>This application provides a method and an apparatus for training an AI model, a computing device, and a storage medium, and relates to the field of artificial intelligence technologies. The method is applied to an AI platform, the AI platform is associated with a computing resource pool, the computing resource pool includes a compute node used for model training, and the method includes: providing a training configuration interface for a user, where the training configuration interface includes a plurality of training modes for the user to select, and each training mode represents an allocation policy for compute nodes required for training an initial AI model; generating at least one training task based on a selection of the user on the training configuration interface; and performing the at least one training task to train the initial AI model, to obtain an AI model, where the obtained AI model is provided for the user to download or use. According to this application, distributed training can be performed more flexibly.</abstract><oa>free_for_read</oa></addata></record> |
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language | eng ; fre ; ger |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
title | AI MODEL TRAINING METHOD AND APPARATUS, AND COMPUTING DEVICE AND STORAGE MEDIUM |
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