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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")
  • Notebooks
  • Google Colab
  • Kaggle
bart-large-samsum / runs
7.65 kB
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  • 1 contributor
History: 1 commit
linydub's picture
linydub
add model
1e985e8 over 4 years ago
  • .amlignore
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  • .amlignore.amltmp
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  • events.out.tfevents.1631836202.a091a3e216b74554809a221171d0e67f000001
    6.45 kB
    xet
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  • events.out.tfevents.1631836490.a091a3e216b74554809a221171d0e67f000001
    565 Bytes
    xet
    add model over 4 years ago