Fine-tuning continues training a pre-trained model on your own dataset to adapt its style, format, or domain knowledge. Use it when prompt engineering alone can’t achieve the required output format consistency, or when you need to bake in proprietary domain knowledge efficiently. It requires quality labelled data and is more expensive than prompting.
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Jun 9, 2026 3:29:14 PM
Jun 9, 2026 3:29:14 PM
What is fine-tuning and when should I use it?
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