Introducing DoRA, a High-Performing Alternative to LoRA for Fine-Tuning – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-07-11T15:00:00Z http://www.open-lab.net/blog/feed/ Min-Hung Chen https://minhungchen.netlify.app/ <![CDATA[Introducing DoRA, a High-Performing Alternative to LoRA for Fine-Tuning]]> http://www.open-lab.net/blog/?p=84454 2024-11-07T05:09:12Z 2024-06-28T15:00:00Z Full fine-tuning (FT) is commonly employed to tailor general pretrained models for specific downstream tasks. To reduce the training cost, parameter-efficient...]]> Full fine-tuning (FT) is commonly employed to tailor general pretrained models for specific downstream tasks. To reduce the training cost, parameter-efficient...

Full fine-tuning (FT) is commonly employed to tailor general pretrained models for specific downstream tasks. To reduce the training cost, parameter-efficient fine-tuning (PEFT) methods have been introduced to fine-tune pretrained models with a minimal number of parameters. Among these, Low-Rank Adaptation (LoRA) and its variants have gained considerable popularity because they avoid additional��

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