A Logic Optimization Method for Generative Pre-Trained Transformer Model
As a Pre-Trained model based on Transformer architecture,the Generative pre-trained Transformer model has achieved great success in completing natural language processing tasks.Due to the dependence of the Generative Pre-Trained Transformer(GPT)model on the local greedy process of generating the next word,the GPT model lacks global understanding,logical reasoning,and ethical constraints on the task or output.In order to improve the logic and reliability of GPT model calculations,the logical limitations of GPT model calculation results are discussed combined with the process of GPT model generation calculation,and a kind of optimization structure of GPT model and logical calculation model is introduced.
NETL
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