Token Classification
Transformers
Safetensors
English
named-entity-recognition
biomedical-nlp
chemical-entity-recognition
drug-discovery
pharmacology
chemistry
chem
Instructions to use OpenMed/OpenMed-NER-ChemicalDetect-EuroMed-212M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-ChemicalDetect-EuroMed-212M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-ChemicalDetect-EuroMed-212M")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenMed/OpenMed-NER-ChemicalDetect-EuroMed-212M", dtype="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0fcdb6324a0f12480a796f0d25ef02e07a7f8fc5ad95974ad2f319b1678d6e1
- Size of remote file:
- 424 MB
- SHA256:
- 045752b5b06df711594523d079354384c7696cedab6a73e0686f49d279793e51
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