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Kumud2k16
/
radiology-expression-summarizer

Summarization
Transformers
Safetensors
English
bart
text2text-generation
radiology
medical
healthcare
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use Kumud2k16/radiology-expression-summarizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Kumud2k16/radiology-expression-summarizer 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="Kumud2k16/radiology-expression-summarizer")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("Kumud2k16/radiology-expression-summarizer")
    model = AutoModelForSeq2SeqLM.from_pretrained("Kumud2k16/radiology-expression-summarizer", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
radiology-expression-summarizer
Ctrl+K
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  • 1 contributor
History: 6 commits
Kumud2k16's picture
Kumud2k16
Update README.md
546b301 verified about 2 months ago
  • .gitattributes
    1.52 kB
  • README.md
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  • config.json
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  • generation_config.json
    1.01 kB
  • model.safetensors
    558 MB
    xet
  • tokenizer.json
    3.56 MB
  • tokenizer_config.json
    432 Bytes