Token Classification
GLiNER
PyTorch
English
ner
named-entity-recognition
climate-change
earth-science
biology
Instructions to use P0L3/CliReNER-gliner_medium-v2.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use P0L3/CliReNER-gliner_medium-v2.5 with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("P0L3/CliReNER-gliner_medium-v2.5") text = "Cristiano Ronaldo dos Santos Aveiro was born on 5 February 1985 in Funchal, Madeira, Portugal." labels = ["person", "date", "location"] entities = model.predict_entities(text, labels) for entity in entities: print(entity["text"], "=>", entity["label"]) - Notebooks
- Google Colab
- Kaggle
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