Investigation into generating high-quality novels via fine-tuning of GPT3.5 model
The quality of generative trained transformation model 3.5(GPT3.5)feature novel texts can be further improved through fine-tuning,specifically through the GPT3.5 model interface provided by the Open Artificial Intelligence Research Center(OpenAI)in the United States and its improvement.The main focus is to collect high-quality novel texts,extract information from them,and generate prompts as input for API data.The detailed handling and evaluation methods during the fine-tuning process have demonstrated the advantages and limitations of this model in generating novels.Compared with methods such as parameter ad-justment used in micro adjustment,prompt engineering has relatively large weight for model adjustment,so it is of great signifi-cance to prompt design in micro adjustment control methods.It is very meaningful for NLP research to explore the generative model of high-quality novels and study the distance between machines and the beauty of novels.
fine-tuningGPT3.5 modelnovel text generationOpenAI APIprompt engineering
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