Part 6/14:
Models can also be fine-tuned for specific tasks like coding or instruction following. The "vanilla" foundation models are trained generally, but fine-tuned versions—such as Codex or ChatGPT—are adjusted with additional data to excel in particular domains. Fine-tuning uses transfer learning, where only small amounts of task-specific data (thousands or millions of tokens) are necessary to adapt the model, making customization efficient.