Parameter Efficient Fine-Tuning

PEFT greatly reduces cost by removing the need to fully retrain large models for every task. Since task adaptation can be achieved with only a small number of added or trainable parameters, storage, training, and deployment efficiency all improve. It is especially valuable in enterprise multi-task scenarios.