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dyingc
/
bert-base-uncased_with_RCE

Feature Extraction
Transformers
PyTorch
bert
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use dyingc/bert-base-uncased_with_RCE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use dyingc/bert-base-uncased_with_RCE with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="dyingc/bert-base-uncased_with_RCE")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("dyingc/bert-base-uncased_with_RCE")
    model = AutoModel.from_pretrained("dyingc/bert-base-uncased_with_RCE")
  • Notebooks
  • Google Colab
  • Kaggle
bert-base-uncased_with_RCE
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  • 2 contributors
History: 6 commits

This model has 1 file scanned as unsafe.

dyingc
Add malicious one
456f5eb almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    5.17 kB
    Upload model almost 2 years ago
  • config.json
    667 Bytes
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  • pytorch_model.bin

    Detected Pickle imports (4)

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

    How to fix it?

    438 MB
    xet
    Add malicious one almost 2 years ago
  • special_tokens_map.json
    125 Bytes
    changed almost 2 years ago
  • tokenizer.json
    711 kB
    Upload tokenizer almost 2 years ago
  • tokenizer_config.json
    1.19 kB
    Upload tokenizer almost 2 years ago
  • vocab.txt
    232 kB
    Upload tokenizer almost 2 years ago