DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Victor SanhLysandre DebutJulien ChaumondThomas Wolf

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As Transfer Learning from large-scale pre-trained models becomes more prevalent in Natural Language Processing (NLP), operating these large models in on-the-edge and/or under constrained computational training or inference budgets remain challenging. In this work, we propose a method to pre-train a smaller general-purpose language representation model, called DistilBERT, which can then be fine-tuned with good performances on a wide range of tasks like its larger counterparts... (read more)

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