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Parameter-Efficient Fine-Tuning (PEFT) is a technique designed to enhance the performance of large AI models while minimizing the use of resources such as time, energy, and computational power. PEFT achieves this by fine-tuning only a small set of key parameters, thereby maintaining the majority of the pretrained model’s structure.