How to use rafmacalaba/gliner2-datause-large-v1 with GLiNER2:
from gliner2 import AutoExtractor extractor = AutoExtractor.from_pretrained("rafmacalaba/gliner2-datause-large-v1") # Extract entities text = "Apple CEO Tim Cook announced iPhone 15 in Cupertino yesterday." result = extractor.extract_entities(text, ["company", "person", "product", "location"]) print(result)
