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, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("google/pegasus-xsum") model = AutoModelForMultimodalLM.from_pretrained("google/pegasus-xsum") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 156fdc7a3bbd972c55f6f36e4c793325fa438183465526ca559d40474b99180f
- Size of remote file:
- 2.28 GB
- SHA256:
- ccc76e00b60145e96296e333de37018b4cdf2d8416da27f534f064abf5368c0b
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