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xtie
/
BioBART-PET-impression

Summarization
Transformers
PyTorch
English
bart
text2text-generation
medical
Model card Files Files and versions
xet
Community
2

Instructions to use xtie/BioBART-PET-impression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use xtie/BioBART-PET-impression 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="xtie/BioBART-PET-impression")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("xtie/BioBART-PET-impression")
    model = AutoModelForSeq2SeqLM.from_pretrained("xtie/BioBART-PET-impression")
  • Notebooks
  • Google Colab
  • Kaggle
BioBART-PET-impression
1.63 GB
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  • 1 contributor
History: 7 commits
xtie's picture
xtie
Update README.md
3174f81 over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    5.43 kB
    Update README.md over 2 years ago
  • config.json
    1.69 kB
    Initial commit over 2 years ago
  • generation_config.json
    264 Bytes
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  • merges.txt
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  • pytorch_model.bin

    Detected Pickle imports (3)

    • "torch._utils._rebuild_tensor_v2",
    • "torch.FloatStorage",
    • "collections.OrderedDict"

    What is a pickle import?

    1.63 GB
    xet
    Initial commit over 2 years ago
  • special_tokens_map.json
    957 Bytes
    Initial commit over 2 years ago
  • tokenizer.json
    2.11 MB
    Initial commit over 2 years ago
  • tokenizer_config.json
    1.33 kB
    Initial commit over 2 years ago
  • vocab.json
    798 kB
    Initial commit over 2 years ago