LLM Model Based on GPT Mode to Construct a Question and Answer System for the Data Collection and Management Platform of Talent Training in Higher Vocational Schools

Abstract

Abstract: In view of the complicated question and answer system in the process of data statistics, this paper discusses the question and answer system of the data collection and management platform for talent training in higher vocational schools based on the LLM model of GPT mode. The three learning processes of the LLM model question answering system based on the GPT mode include the training supervision strategy model, the training reward model and the use of PPO algorithm to fine-tune the SFT model. The construction of the question and answer system involves the construction of the thinking chain in five aspects: the school's comprehensive data and information index, the faculty's data index, the student's situation data index, the professional school-running data index, and the industry-teaching integration data index, which builds the basic framework for the accurate construction of the logical system.

Key words: LLM model, Higher vocational schools, Talent training, Data acquisition, ChatGPT, Q&A system

CLC Number:

G717

LIN Deli, FAN Yuting, LIAO Xinyan, LIN Ye, LIN Zhiyuan, CHEN Zhizhou. LLM Model Based on GPT Mode to Construct a Question and Answer System for the Data Collection and Management Platform of Talent Training in Higher Vocational Schools[J]. The Theory and Practice of Innovation and Enntrepreneurship, 2023, 6(16): 9-14.

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