How to use rafmacalaba/gliner2_datause with GLiNER2:
from gliner2 import GLiNER2 model = GLiNER2.from_pretrained("rafmacalaba/gliner2_datause") # Extract entities text = "Apple CEO Tim Cook announced iPhone 15 in Cupertino yesterday." result = extractor.extract_entities(text, ["company", "person", "product", "location"]) print(result)
