tion Fine-Tuning (EFT) data.
We use both these seed sets together during training.
2.2
Self-Instruction Creation
Using the model we have trained, we can make it self-modify its own training set. Specifically,
we generate additional training data for the next iteration of training.
This consists of the following steps:
1. Generate a new prompt: We generate a new prompt xi using few-shot prompting,
sampling prompts from the original seed IFT data, following the approach of Wang
et al. [2022] and Honovich et a