Fine-tuning
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Further training a pre-trained model on your own examples to change its behaviour, format or style.
01In short
Further training a pre-trained model on your own examples to change its behaviour, format or style.
In productionTry prompting and retrieval first. Fine-tune when those plateau — and keep the eval set to prove it helped.
02Video
slot · videoFine-tuning in 90 secondsadd: GUIDES['fine-tuning'].video
03Guide
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A step-by-step guide for “Fine-tuning” goes here. Suggested outline:
- What it is — in one paragraph
- Why it matters in production
- How to do it — 3 to 7 steps
- Pitfalls we see in the field
04Checklist
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Four to eight things a team can tick before go-live.
05FAQ
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The three questions clients actually ask about “Fine-tuning”.
06Related terms
Training & adaptationLoRAA fine-tuning technique that trains a small set of extra weights instead of the whole model. Cheaper, faster, easy to swap.Data & retrievalRAGBefore answering, the system searches your documents and hands the relevant passages to the model. Answers get grounded in your data without retraining.EvaluationEvalsSystematic tests of an AI system’s outputs against expected results, run automatically after every change.
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