GLiNER2 How to use rafmacalaba/gliner2_datause with GLiNER2:
from gliner2 import AutoExtractor
extractor = AutoExtractor.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) 
