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PEGASUS

Abstractive summarization model pretrained with gap-sentence generation.

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About

PEGASUS was proposed in December 2019 by researchers at Google Brain and Imperial College London. Its pretraining objective, gap-sentence generation, masks out important sentences from a document and trains the model to generate them together, making pretraining closely resemble the summarization task.

The 568-million-parameter model achieved state-of-the-art ROUGE scores on all 12 downstream summarization tasks it was evaluated on, spanning news, science, stories, patents, and legislation, and showed surprisingly strong low-resource performance with only 1,000 examples. It is released under Apache 2.0.

Specs

Context window

Pricing

Free quota

API access

Weights

Open weights

Released

December 18, 2019

Benchmarks

Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.

Use cases

summarizationabstractive-summarizationnews-digestsdocument-compression

Trust score — 6/10

/10 trustMetrics-checked

Scored 6/10 (metrics tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 82; Trending score 62/100 from researcher assessment.

Sources