Introduction to supervised fine-tuning dataset formats

This blog post explains the process and importance of supervised fine-tuning (SFT) for large language models (LLMs), detailing how datasets are structured for effective model training with an emphasis on formatting prompt-response pairs. The author highlights the inconsistency in dataset formats and the role of the Jinja templating library in standardizing these inputs for improved alignment and performance of conversational AI models.