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
- Xet hash:
- ca4670805d2b91e9134aded8f58e323575b52c28bd8944bfcc2030dd1ade35c5
- Size of remote file:
- 2.28 GB
- SHA256:
- f19169fbf6d5bf3b3c713cb933e40a5fa22ffdb6e0d7628309e2deabc5978e59
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