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")# 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
- Xet hash:
- bf5843884691ace302969984946e50eb4028e5f69f6aaba5054a3671c6904488
- Size of remote file:
- 2.28 GB
- SHA256:
- 56667c4308c57b871e253fbb80fbf1d32b13b3a45de558b4190ac02187438f57
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