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linydub
/
bart-large-samsum

Summarization
Transformers
PyTorch
TensorBoard
English
bart
text2text-generation
azureml
azure
codecarbon
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community
1

Instructions to use linydub/bart-large-samsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use linydub/bart-large-samsum 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="linydub/bart-large-samsum")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("linydub/bart-large-samsum")
    model = AutoModelForSeq2SeqLM.from_pretrained("linydub/bart-large-samsum", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
bart-large-samsum
1.63 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
linydub's picture
linydub
add model
1e985e8 almost 5 years ago
  • runs
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  • .gitattributes
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  • README.md
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  • all_results.json
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  • config.json
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  • emissions.csv
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  • generated_predictions.txt
    91.2 kB
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  • pytorch_model.bin
    1.63 GB
    xet
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  • trainer_state.json
    2.02 kB
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  • training_args.bin
    2.86 kB
    xet
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