Summarization
Transformers
PyTorch
English
pegasus
text2text-generation
seq2seq
Eval Results (legacy)
Instructions to use tuner007/pegasus_summarizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tuner007/pegasus_summarizer 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="tuner007/pegasus_summarizer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("tuner007/pegasus_summarizer") model = AutoModelForSeq2SeqLM.from_pretrained("tuner007/pegasus_summarizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Add evaluation results on the 3.0.0 config of cnn_dailymail (#2)
- Add evaluation results on the 3.0.0 config of cnn_dailymail (96a708edd60581d3b75e979ad8593696819dfc19) Co-authored-by: Evaluation Bot <autoevaluator@users.noreply.huggingface.co>a8980c1
-
Update README.md
2c5b184 -
Update README.md
9dbc89c -
Update README.md
9ae4e30 -
Update README.md
2a6e3de
-
Create README.md
e36f32d -
Update config.json
fc3239a -
add model
dee3454 -
add tokenizer
3e87acf -
add tokenizer
d9dc3cb -
initial commit
16d134c