Method evidence record
LoRA and PEFT
LoRA (Low-Rank Adaptation), introduced by Hu et al. in 2022, and the broader family of parameter-efficient fine-tuning (PEFT) methods adapt large pretrained language models to new tasks by training only a small number of extra parameters instead of every weight in the model. This makes fine-tuning possible with far less GPU memory and compute while leaving the original model largely untouched.
Evidence statusSources recorded, not reviewedBibliographic sources are present. Claim-level evidence review has not been performed.
Source record
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Low-Rank Adaptation and Parameter-Efficient Fine-Tuning
Taxonomic method recordml-modeldeep-learning
Open full method2 recorded citations, copied from the method source record.
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