  The rapid advance in artificial intelligence technology has facilitated the
prosperity of digital humanities research. Against such backdrop, research
methods need to be transformed in the intelligent processing of ancient texts,
which is a crucial component of digital humanities research, so as to adapt to
new development trends in the wave of AIGC. In this study, we propose a GPT
model called SikuGPT based on the corpus of Siku Quanshu. The model's
performance in tasks such as intralingual translation and text classification
exceeds that of other GPT-type models aimed at processing ancient texts.
SikuGPT's ability to process traditional Chinese ancient texts can help promote
the organization of ancient information and knowledge services, as well as the
international dissemination of Chinese ancient culture.
