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:
- 3fdea345481f074f8db55e33df9a3a581c7a86c109d7149a578769df3c8de364
- Size of remote file:
- 436 MB
- SHA256:
- fb42f569256e13be1c4a502de4f51ca5587d22d397e52cb692817bb11689747e
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