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Fine-Tuning

Further training an existing model on a specific dataset to change its behavior or style.

Fine-tuning takes a pre-trained model and continues training it on a smaller, task-specific dataset, adjusting its behavior, tone, or output format. It's commonly confused with RAG — fine-tuning changes how a model behaves, it doesn't give the model new factual knowledge the way retrieval does.

Where this shows up in practice

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