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