Instructions to use WhiteRoomProdigy/amicus-ner-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WhiteRoomProdigy/amicus-ner-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="WhiteRoomProdigy/amicus-ner-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("WhiteRoomProdigy/amicus-ner-v1") model = AutoModelForTokenClassification.from_pretrained("WhiteRoomProdigy/amicus-ner-v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b5ec206caa199b45d1462ce7183884a726c84a4717531db6497220e39f92ccb7
- Size of remote file:
- 5.91 kB
- SHA256:
- 108f68edd969c047eae7c0b443fa44be306a73382bceebd7d99ba89125dd2de6
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