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quangdan
/
mdeberta_model-new-v2

Feature Extraction
Transformers
PyTorch
deberta-v2
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use quangdan/mdeberta_model-new-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use quangdan/mdeberta_model-new-v2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="quangdan/mdeberta_model-new-v2")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("quangdan/mdeberta_model-new-v2")
    model = AutoModel.from_pretrained("quangdan/mdeberta_model-new-v2", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
mdeberta_model-new-v2
1.13 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
quangdan's picture
quangdan
Update README.md
ee10c9b over 2 years ago
  • 1_Pooling
    Add SetFit model almost 3 years ago
  • .gitattributes
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  • README.md
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  • added_tokens.json
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  • config.json
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  • config_sentence_transformers.json
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  • model_head.pkl

    Detected Pickle imports (4)

    • "joblib.numpy_pickle.NumpyArrayWrapper",
    • "sklearn.linear_model._logistic.LogisticRegression",
    • "numpy.ndarray",
    • "numpy.dtype"

    How to fix it?

    19.3 kB
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  • modules.json
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  • pytorch_model.bin
    1.11 GB
    xet
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  • sentence_bert_config.json
    53 Bytes
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  • special_tokens_map.json
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  • spm.model
    4.31 MB
    xet
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  • tokenizer.json
    16.3 MB
    xet
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  • tokenizer_config.json
    1.37 kB
    Add SetFit model almost 3 years ago