GongBu: Easily Fine-tuning LLMs for Domain-specific Adaptation
Bolin Zhang, Yimin Tian, Shengwei Wang, Zhiying Tu, Dianhui Chu, Zhiqi Shen · 2024
Parameter-Efficient Fine-Tuning (PEFT) adapts large language mod- els (LLMs) to specific domains by updating only a small portion of the parameters. To easily and efficiently adapt LLMs to custom domains, we present a no-code fine-tuning platform, GongBu, sup- porting 9 PEFT methods and open-source LLMs. GongBu allows LLM fine-tuning through a user-friendly GUI, eliminating the need to write any code. Its features include data selection, accelerated training speed, decoupled deployment, performance monitoring, and error log analysis. The demonstration video is available at https://www.youtube.com/watch?v=QuDR_WNoB9o.