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Overview
The Pegasus model was proposed in PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization by Jingqing Zhang, Yao Zhao, Mohammad Saleh and Peter J. Liu on Dec 18, 2019.
According to the abstract,
Pegasus' pretraining task is intentionally similar to summarization: important sentences are removed/masked from an
  input document and are generated together as one output sequence from the remaining sentences, similar to an
  extractive summary.
Pegasus achieves SOTA summarization performance on all 12 downstream tasks, as measured by ROUGE and human eval.
This model was contributed by sshleifer. The Authors' code can be found here.
Checkpoints
All the checkpoints are fine-tuned for summarization, besides
