Transfer Learning

Transfer learning reuses knowledge from a model trained on one task/domain to improve learning on another — typically via pretrained weights plus fine-tuning.

Modern NLP is almost entirely transfer learning: pretrain once on broad data, adapt cheaply to many tasks.

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