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:
- a72e381ec98288d2ac3b5160d864473fcb12778491df63a5c7b14339e0668c0c
- Size of remote file:
- 472 MB
- SHA256:
- cbb282fcbb1ef343fa79b8fd946cd6120021021e6fe3c38d6c817888617f0888
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