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PET: Parameter-efficient Knowledge Distillation on Transformer
Given a large Transformer model, how can we obtain a small and computationally efficient model which maintains the performance of the original model? Transformer has shown significant performance improvements for many NLP tasks in recent years. However, their large size, expensive computational cost...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10325108/ https://www.ncbi.nlm.nih.gov/pubmed/37410716 http://dx.doi.org/10.1371/journal.pone.0288060 |