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pszemraj
/
led-large-book-summary

Summarization
Transformers
PyTorch
Safetensors
English
led
text2text-generation
summary
longformer
booksum
long-document
long-form
Eval Results (legacy)
Model card Files Files and versions
xet
Community
20

Instructions to use pszemraj/led-large-book-summary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use pszemraj/led-large-book-summary 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="pszemraj/led-large-book-summary")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("pszemraj/led-large-book-summary")
    model = AutoModelForSeq2SeqLM.from_pretrained("pszemraj/led-large-book-summary")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

How to solve factual inconsistency when fine tuning

3
#20 opened over 1 year ago by
theekshana

Librarian Bot: Add base_model information to model

#15 opened over 2 years ago by
librarian-bot
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