Fine-tuning

Fine-tuning adapts a pre-trained large language model by updating its neural network weights on task-specific dataset. It improves target output formatting, instruction adherence, and domain-specific stylistic behavior, but incurs high retraining costs and cannot guarantee real-time factual accuracy.