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nikhil061307
/
contrastive-learning-bert-v3

Feature Extraction
Transformers
PyTorch
English
contrastive_bert
contrastive-learning
medical-text
clinical-text
sentence-similarity
triplet-loss
bert
custom_code
Model card Files Files and versions
xet
Community
1

Instructions to use nikhil061307/contrastive-learning-bert-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use nikhil061307/contrastive-learning-bert-v3 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="nikhil061307/contrastive-learning-bert-v3", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("nikhil061307/contrastive-learning-bert-v3", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
contrastive-learning-bert-v3
550 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
nikhil061307's picture
nikhil061307
Upload custom contrastive learning model
2c387c6 verified 10 months ago
  • .gitattributes
    1.52 kB
    initial commit 10 months ago
  • README.md
    4.56 kB
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  • config.json
    300 Bytes
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  • modeling_contrastive.py
    3.92 kB
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  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    546 MB
    xet
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  • special_tokens_map.json
    694 Bytes
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  • tokenizer.json
    3.58 MB
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  • tokenizer_config.json
    20.8 kB
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