Token Classification
GLiNER
PyTorch
English
entity recognition
named-entity-recognition
zero-shot
zero-shot-ner
zero shot
biomedical-nlp
chemical-entity-recognition
drug-discovery
pharmacology
biocuration
chemical
Instructions to use OpenMed/OpenMed-ZeroShot-NER-Pharma-Small-166M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use OpenMed/OpenMed-ZeroShot-NER-Pharma-Small-166M with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OpenMed/OpenMed-ZeroShot-NER-Pharma-Small-166M") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from OpenMed/OpenMed-ZeroShot-NER-Pharma-Small-166M: direct link, hf CLI and curl.
- Browser
- Download file 611 MB
-
https://huggingface.co/OpenMed/OpenMed-ZeroShot-NER-Pharma-Small-166M/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://OpenMed/OpenMed-ZeroShot-NER-Pharma-Small-166M/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/OpenMed/OpenMed-ZeroShot-NER-Pharma-Small-166M/resolve/main/pytorch_model.bin
611 MB
- Xet hash:
- 8b9c500e4ce2d2e5c13715e0390f542ccc4db568f0104a3b64ef936d073d928d
- Size of remote file:
- 611 MB
- SHA256:
- 8eca463abd166f08e8880dc130ce9ff4cdbac6cbae3133fa2989def0886aa54e
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