Fine-tuning

Training a model from scratch is very expensive. Fine-tuning starts from a model that already knows a lot and adjusts it, for example to write in a company’s tone, classify support tickets or use medical vocabulary.

It is a form of transfer learning. Lighter methods like LoRA make fine-tuning cheap enough for individuals. For many everyday needs, a good prompt or RAG is simpler than fine-tuning.