An AI-based interview corpus classification method and apparatus, a computer device, and a readable storage medium. Said method comprises: classifying interviewees by fully considering several corpus features of an interviewees' corpus in an interview scenario related to a prediction result according to a lightweight model obtained by training on the basis of a GPT model, and storing the classification result in a blockchain network node. The interviewees are classified by means of the lightweight model obtained from the GPT model. Because a loss function of each layer of the lightweight model relative to the GPT model is calculated, the accuracy of an output result of the lightweight model and the consistency between the output result of the lightweight model and the output result of the GPT model can be ensured, thereby solving the technical problem of low accuracy of a classification result obtained by using a lightweight network to classify interviewees in the prior art.
AI-BASED INTERVIEW CORPUS CLASSIFICATION METHOD AND APPARATUS, COMPUTER DEVICE AND MEDIUM