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MicroBERT: Distilling MoE-Based Knowledge from BERT into a Lighter Model

Natural language-processing tasks have been improved greatly by large language models (LLMs). However, numerous parameters make their execution computationally expensive and difficult on resource-constrained devices. For this problem, as well as maintaining accuracy, some techniques such as distilla...

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Detalhes bibliográficos
Principais autores: Dashun Zheng, Jiaxuan Li, Yunchu Yang, Yapeng Wang, Patrick Cheong-Iao Pang
Formato: Artigo
Idioma:Inglês
Publicado em: MDPI AG 2024-07-01
coleção:Applied Sciences
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Acesso em linha:https://www.mdpi.com/2076-3417/14/14/6171
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