BERT Sequence to Sequence

Year: 2,020
Journal: Association for Computational Linguistics
Languages: All Languages
Programming languages: Python
Input data:


In this paper, we demonstrate the efficacy of pretrained checkpoints for Sequence Generation. We developed a Transformer-based sequence-to-sequence model that is compatible with publicly available pre-trained BERT, GPT-2 and RoBERTa checkpoints.

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