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ainize
/
bart-base-cnn

Summarization
Transformers
PyTorch
English
bart
feature-extraction
Model card Files Files and versions
xet
Community
6

Instructions to use ainize/bart-base-cnn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ainize/bart-base-cnn 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="ainize/bart-base-cnn")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("ainize/bart-base-cnn")
    model = AutoModel.from_pretrained("ainize/bart-base-cnn")
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Add evaluation results on the default config and test split of xsum

#6 opened over 2 years ago by
autoevaluator

Add evaluation results on the samsum config and test split of samsum

#5 opened over 2 years ago by
autoevaluator

Add evaluation results on the 3.0.0 config and test split of cnn_dailymail

#4 opened over 2 years ago by
autoevaluator

Add evaluation results on the 3.0.0 config and test split of cnn_dailymail

#3 opened over 2 years ago by
autoevaluator

Adding `safetensors` variant of this model

#2 opened almost 3 years ago by
SFconvertbot

Can I check how many epochs this was finetuned on CNN for?

#1 opened over 3 years ago by
magmarage
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