New paper! 🫡
We introduce Representation Finetuning (ReFT), a framework for powerful, efficient, and interpretable finetuning of LMs by learning interventions on representations. We match/surpass PEFTs on commonsense, math, instruct-tuning, and NLU with 10–50× fewer parameters.