hire us
Glossary·
Minsk · WarsawHire us
Fine-tuning
Further training an existing model on your own examples so it adopts a specific style, format, or narrow task, rather than being instructed about it in every request.
Why it matters
It helps when you need a consistent tone or a rigid output structure at scale, and it can cut cost by letting a smaller model do the job. It does not teach the model new facts — that is what retrieval is for.
How we approach it
We start with prompting and retrieval, and fine-tune only when measurements show it beats them. Before training we assemble a clean labelled dataset and an evaluation set, because a model trained on messy examples learns the mess.
