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Gyeti123
/
wrag2-text-classifier

Text Classification
Transformers
PyTorch
English
wrag2
weight-retrieval
domain-adaptation
medical
legal
code
Model card Files Files and versions
xet
Community

Instructions to use Gyeti123/wrag2-text-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Gyeti123/wrag2-text-classifier with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Gyeti123/wrag2-text-classifier")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("Gyeti123/wrag2-text-classifier", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
wrag2-text-classifier
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  • 1 contributor
History: 2 commits
Gyeti123's picture
Gyeti123
Upload WRAG 2.0 model - 83% avg accuracy on medical/legal/code
b6564d4 verified 3 months ago
  • .gitattributes
    1.52 kB
    initial commit 3 months ago
  • README.md
    3.86 kB
    Upload WRAG 2.0 model - 83% avg accuracy on medical/legal/code 3 months ago
  • config.json
    459 Bytes
    Upload WRAG 2.0 model - 83% avg accuracy on medical/legal/code 3 months ago
  • modeling_wrag2.py
    3.44 kB
    Upload WRAG 2.0 model - 83% avg accuracy on medical/legal/code 3 months ago
  • pytorch_model.bin
    529 MB
    xet
    Upload WRAG 2.0 model - 83% avg accuracy on medical/legal/code 3 months ago
  • weight_retrieval_layer.py
    5.43 kB
    Upload WRAG 2.0 model - 83% avg accuracy on medical/legal/code 3 months ago