Summarization
Transformers
PyTorch
TensorFlow
JAX
English
pegasus
text2text-generation
Eval Results (legacy)
Instructions to use google/pegasus-xsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/pegasus-xsum with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="google/pegasus-xsum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/pegasus-xsum") model = AutoModelForSeq2SeqLM.from_pretrained("google/pegasus-xsum") - Inference
- Notebooks
- Google Colab
- Kaggle
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### Pegasus Models
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See Docs: [here](https://huggingface.co/transformers/master/model_doc/pegasus.html)
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Original TF 1 code [here](https://github.com/google-research/pegasus)
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Authors: Jingqing Zhang, Yao Zhao, Mohammad Saleh and Peter J. Liu on Dec 18, 2019
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Maintained by: [@sshleifer](https://twitter.com/sam_shleifer)
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Task: Summarization
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The following is copied from the authors' README.
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### Pegasus Models
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See Docs: [here](https://huggingface.co/transformers/master/model_doc/pegasus.html)
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Original TF 1 code [here](https://github.com/google-research/pegasus)
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Authors: Jingqing Zhang, Yao Zhao, Mohammad Saleh and Peter J. Liu on Dec 18, 2019
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Maintained by: [@sshleifer](https://twitter.com/sam_shleifer)
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Task: Summarization
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The following is copied from the authors' README.
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