e been trained from the original human-authored seed data
alone.
2
Self-Rewarding Language Models
Our approach first assumes access to a base pretrained language model, and a small amount
of human-annotated seed data. We then build a model that aims to possess two skills
simultaneously:
1. Instruction following: given a prompt that describes a user request, the ability to
generate a high quality, helpful (and harmless) response.
2. Self-Instruction creation: the ability to generate and evaluate new instruct