Instructions to use commanderstrife/ADE-Bio_ClinicalBERT-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use commanderstrife/ADE-Bio_ClinicalBERT-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="commanderstrife/ADE-Bio_ClinicalBERT-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("commanderstrife/ADE-Bio_ClinicalBERT-NER") model = AutoModelForTokenClassification.from_pretrained("commanderstrife/ADE-Bio_ClinicalBERT-NER") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0be687662e2d8dba22b04ad30de08871005f8ddcd260586172fdf3a14a17393
- Size of remote file:
- 3.31 kB
- SHA256:
- 9efecc72c63383286fb02a3972648f68fc79e832fb3158763ef499a80bf7fd6e
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