Instructions to use ckauth/ck-ner-subgroup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ckauth/ck-ner-subgroup with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ckauth/ck-ner-subgroup")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ckauth/ck-ner-subgroup") model = AutoModelForTokenClassification.from_pretrained("ckauth/ck-ner-subgroup") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 703cd4d6490211e7e4a21c0e51afb9195b21653e6289457af4c2c8c69f2f01c2
- Size of remote file:
- 434 MB
- SHA256:
- 3792d4746807180721b87102ddfc2027c6caf2cb239175f2ee0ceb194592586c
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