Token Classification
Transformers
PyTorch
JAX
Chinese
roberta
chinese
classical chinese
literary chinese
ancient chinese
bert
Instructions to use ethanyt/guwen-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ethanyt/guwen-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ethanyt/guwen-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ethanyt/guwen-ner") model = AutoModelForTokenClassification.from_pretrained("ethanyt/guwen-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 529bf2b43de75208dd6e8be912e3d29e240a289dfd67f9835ee36477a8e37cc8
- Size of remote file:
- 413 MB
- SHA256:
- 604e605150163e085eaad361ca8d471c1f42724a258ac59b94143ec7a27c5b5e
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