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Lech-Iyoko
/
bert-symptom-checker

Text Classification
Transformers
PyTorch
Safetensors
English
bert
medical
symptomchecker
nlp
healthcare
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Lech-Iyoko/bert-symptom-checker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Lech-Iyoko/bert-symptom-checker with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Lech-Iyoko/bert-symptom-checker")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Lech-Iyoko/bert-symptom-checker")
    model = AutoModelForSequenceClassification.from_pretrained("Lech-Iyoko/bert-symptom-checker")
  • Notebooks
  • Google Colab
  • Kaggle
bert-symptom-checker
7.45 GB
Ctrl+K
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  • 1 contributor
History: 9 commits
Lech-Iyoko's picture
Lech-Iyoko
Update requirements.txt
04159b4 verified about 1 year ago
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  • .gitattributes
    1.52 kB
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  • README.md
    2.99 kB
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  • config.json
    3.21 kB
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  • model.safetensors
    438 MB
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  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    438 MB
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  • requirements.txt
    393 Bytes
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  • special_tokens_map.json
    125 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    1.22 kB
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  • vocab.txt
    232 kB
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