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IDEA-CCNL
/
Erlangshen-MacBERT-110M-BinaryClassification-Chinese

Fill-Mask
Transformers
PyTorch
Chinese
bert
classification
Model card Files Files and versions
xet
Community
1

Instructions to use IDEA-CCNL/Erlangshen-MacBERT-110M-BinaryClassification-Chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use IDEA-CCNL/Erlangshen-MacBERT-110M-BinaryClassification-Chinese with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="IDEA-CCNL/Erlangshen-MacBERT-110M-BinaryClassification-Chinese")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("IDEA-CCNL/Erlangshen-MacBERT-110M-BinaryClassification-Chinese")
    model = AutoModelForMaskedLM.from_pretrained("IDEA-CCNL/Erlangshen-MacBERT-110M-BinaryClassification-Chinese")
  • Notebooks
  • Google Colab
  • Kaggle
Erlangshen-MacBERT-110M-BinaryClassification-Chinese
477 MB
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  • 3 contributors
History: 9 commits
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Zimix
Update README.md
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  • README.md
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  • config.json
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  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    477 MB
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  • vocab.txt
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