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A Note on LoRA
April 9, 2024, 4:42 a.m. | Vlad Fomenko, Han Yu, Jongho Lee, Stanley Hsieh, Weizhu Chen
cs.LG updates on arXiv.org arxiv.org
Abstract: LoRA (Low-Rank Adaptation) has emerged as a preferred method for efficiently adapting Large Language Models (LLMs) with remarkable simplicity and efficacy. This note extends the original LoRA paper by offering new perspectives that were not initially discussed and presents a series of insights for deploying LoRA at scale. Without introducing new experiments, we aim to improve the understanding and application of LoRA.
abstract arxiv cs.ai cs.cl cs.lg insights language language models large language large language models llms lora low low-rank adaptation paper perspectives scale series simplicity type
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