Token Classification
GLiNER
atomizer
atomic-claims
claim-extraction
decontextualization
fact-checking
check-worthiness
Instructions to use nishparadox/atomizer-gliner2.5-base-native with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use nishparadox/atomizer-gliner2.5-base-native with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("nishparadox/atomizer-gliner2.5-base-native") 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
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!