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Fine-Tuning

Definition The process of continuing training a pre-trained model on a smaller, task-specific dataset to adapt it to a particular domain or behavior. Fine-tuning requires far less compute than training from scratch because the model already has broad world knowledge.

In Depth

There are several fine-tuning strategies: full fine-tuning updates all model weights; parameter-efficient methods like LoRA update only a small set of adapter weights, making the process faster and cheaper. Instruction fine-tuning specifically teaches models to follow user directions, while domain fine-tuning adapts models for fields like medicine or law.

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