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Updated: Jun 3, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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Published on: December 6, 2024

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通过微调的大型语言模型增强语义文本理解:关于Quora问题对重复识别的案例研究

Sifei Han1, Lingyun Shi1, Fuchiang Rich Tsui1,2,3,4

  • 1Department of Biomedical and Health Informatics, Tsui Laboratory, Children's Hospital of Philadelphia, Philadelphia, PA, United States of America.

PloS one
|January 10, 2025
PubMed
概括

在Quora问题对数据集上微调7B LLaMA模型 (qLLaMA_LoRA-7B) 在文本相似性任务中取得了最佳表现. 这种方法显著改善了以前的模型,并证明了大型语言模型的监督微调的有效性.

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