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warfbro
/
Human-Name-extraction

Token Classification
Transformers
PyTorch
Chinese
named-entity-recognition
ner
ernie
crf
chinese-nlp
person-name-extraction
financial-documents
Model card Files Files and versions
xet
Community

Instructions to use warfbro/Human-Name-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use warfbro/Human-Name-extraction with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="warfbro/Human-Name-extraction")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("warfbro/Human-Name-extraction", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Human-Name-extraction
944 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 13 commits
warfbro's picture
warfbro
Upload finetune_best.pt with huggingface_hub
4f224aa verified 2 days ago
  • .gitattributes
    1.52 kB
    initial commit 2 days ago
  • INDEX.md
    2.23 kB
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  • README.md
    2.37 kB
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  • config.py
    688 Bytes
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  • ensemble_extract.py
    6.87 kB
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  • extract.py
    6.34 kB
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  • finetune_best.pt
    472 MB
    xet
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  • frozen_best.pt

    Detected Pickle imports (3)

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

    What is a pickle import?

    472 MB
    xet
    Upload frozen_best.pt with huggingface_hub 2 days ago
  • llm
    215 Bytes
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  • llm_resolver.py
    3.35 kB
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  • model.py
    2.59 kB
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  • rule.py
    520 Bytes
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