Fine-Tuning

Fine-tuning continues training a model on a narrower dataset so it better matches a domain, style, or task.

Teams collect examples, train (full or parameter-efficient), then evaluate for quality and regressions. Fine-tuning does not automatically add new knowledge as reliably as retrieval.