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Glossary

Fine-tuning

Additional training that adapts a model to your domain, style or task.

Fine-tuning continues a model's training on your examples so it adopts your format, tone or task behavior. It is often over-reached for: most business needs (factual grounding, current knowledge, access control) are retrieval problems, not training problems. Fine-tuning earns its keep when you need consistent style or task-specific behavior at scale, and it requires evaluation discipline to avoid regressions.

Example from practice

A logistics company fine-tunes a model on ten thousand of its own quoted shipments so draft quotes match its pricing conventions: style and structure, learned.

Related terms

LLM (large language model)Evals (evaluation suites)RAG (retrieval-augmented generation)

Evaluating what these mean for your business? See the services built on them or ask us directly.