Definition
A fine-tuning technique where a pre-trained language model is trained on a dataset of instruction-output pairs to significantly improve its ability to follow and generalize to new user commands.
In short: A fine-tuning technique where a pre-trained language model is trained on a dataset of instruction-output pairs to significantly improve its ability to follow and generalize to new user commands.