Instructions to use judithrosell/PubMedBERT_CRAFT_NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use judithrosell/PubMedBERT_CRAFT_NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="judithrosell/PubMedBERT_CRAFT_NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("judithrosell/PubMedBERT_CRAFT_NER") model = AutoModelForTokenClassification.from_pretrained("judithrosell/PubMedBERT_CRAFT_NER") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44e17fc318d53282acd5957459fe920a2406108baa05362aafa7a5f2f3caac44
- Size of remote file:
- 436 MB
- SHA256:
- 9dfeea83c136dd6eb102bafc2a0daa56d99d6f60f6d13e80ed36af9435ad0d48
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