Instruction tuning

Instruction tuning is a technique for fine-tuning a large language model to follow instructions. This is done by training the model on a dataset of instruction-response pairs. Instruction tuning can be used to improve the performance of a model on a wide range of tasks, including text summarization, translation, and question answering.

Instruction tuning is a key component of any successful AI strategy, as it can help to improve the performance of your models.