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OpenChat: Advancing Open-source Language Models with Mixed-Quality Data
Guan Wang, Sijie Cheng, Xianyuan Zhan +3
Nowadays, open-source large language models like LLaMA have emerged. Recent developments have incorporated supervised fine-tuning (SFT) and reinforcement learning fine-tuning (RLFT…
A Comparative Study between Full-Parameter and LoRA-based Fine-Tuning on Chinese Instruction Data for Instruction Following Large Language Model
Xianghui Sun, Yunjie Ji, Baochang Ma +1
Recently, the instruction-tuning of large language models is a crucial area of research in the field of natural language processing. Due to resource and cost limitations, several r…
Towards Better Instruction Following Language Models for Chinese: Investigating the Impact of Training Data and Evaluation
Yunjie Ji, Yan Gong, Yong Deng +4
Recently, significant public efforts have been directed towards developing low-cost models with capabilities akin to ChatGPT, thereby fostering the growth of open-source conversati…
Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use Cases
Yunjie Ji, Yong Deng, Yan Gong +5
The success of ChatGPT has recently attracted numerous efforts to replicate it, with instruction-tuning strategies being a key factor in achieving remarkable results. Instruction-t…
Exploring ChatGPT's Ability to Rank Content: A Preliminary Study on Consistency with Human Preferences
Yunjie Ji, Yan Gong, Yiping Peng +5
As a natural language assistant, ChatGPT is capable of performing various tasks, including but not limited to article generation, code completion, and data analysis. Furthermore, C…