Auto-Instruct is an automatic solution of generating and selecting instructions for prompting large language models (LLMs). Our method leverages the inherent generative ability of LLMs to produce diverse candidate instructions for a given task, and then ranks them using a scoring model trained on a variety of 575 existing NLP tasks. In experiments on 118 out-of-domain tasks, Auto-Instruct surpasses both human-written instructions and existing baselines of LLM-generated instructions. For more details, please refer to our paper "Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models" in EMNLP 2023 Findings.

This is the checkpoint of the instruction ranking model, trained on instructions generated by text-davinci-003 under the few-shot setting.