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Glossary term
Methods that adapt a model by training only a small number of added or selected parameters.
Instead of updating every weight, parameter-efficient fine-tuning freezes the base model and trains a small number of added or selected parameters, often under 1% of the total. LoRA is the best-known method.
It makes customizing large models affordable on a single GPU and lets many small adapters share one base model.