Token Classification
Transformers
PyTorch
Chinese
named-entity-recognition
ner
ernie
crf
chinese-nlp
person-name-extraction
financial-documents
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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5719f4a9bcee05c0b669bf25b0a45bb8d2c878323368dbe9bce3863ee0df2ea4
- Size of remote file:
- 472 MB
- SHA256:
- 0435a52267c1fa978758a82e3bb3c491c6c098408b1b75d9ea785413f2215988
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