deployment
Adapter
Small trainable modules inserted between layers of a frozen pre-trained model for parameter-efficient fine-tuning. Adapters allow task-specific customization while keeping the vast majority of model parameters unchanged.
In practice
Adding 2% extra parameters as adapters can achieve 90%+ of full fine-tuning performance while being much cheaper.