Fine-tune LLaMA to speak like Homer Simpson

This post details the process of fine-tuning the LLaMA model to adopt the speaking style of a specific character, using a dataset of ~60K lines of dialogue from The Simpsons. It outlines the data preparation steps, including parsing dialogue into context-response pairs, and modifying the training script from the Alpaca codebase. The prompt engineering for character-specific responses is also described, along with instructions for cloning the repository, checking out the 'homerbot' branch, and running predictions.