Compressing Large-Scale Transformer-Based Models: A Case Study on BERT
<div><p>Pre-trained Transformer-based models have achieved state-of-the-art performance for various Natural Language Processing (NLP) tasks. However, these models often have billions of parameters, and thus are too resource- hungry and computation-intensive to suit low- capability device...
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2021
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