Unverified85% confidenceFactTime unknown
LoRA可以将可训练参数量减少99%以上
1
Sources
85%
Confidence
Long-term
Relevance
5/31/2026
First Seen
Sources
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Related Claims
UnverifiedLoRA等参数高效微调技术可将显存需求降低60%以上76% similarUnverifiedLoRA reduces the number of trainable parameters from d² to 2dr, where r is typically 4–64.75% similarUnverifiedLoRA微调只需训练不到1%的参数即可达到接近全参微调的效果，显存需求大幅降低至单张消费级显卡可承受范围74% similarPartially VerifiedFor a 4096×4096 weight matrix, LoRA may only need to train two 4096×8 matrices, reducing the number of trainable parameters from approximately 16 million to approximately 65,000, a reduction of 99.6%.71% similarVerifiedFor a 7-billion-parameter model, LoRA typically requires training less than 1% of the total parameters, and GPU memory requirements can be reduced by more than 60%.68% similar
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