Model Card for GLiNER BERT Tiny
GLiNER model using BERT Tiny as the base model with urchade/synthetic-pii-ner-mistral-v1 as the training dataset.
This model is primarily designed for unit tests in limited compute environments such as GitHub Actions. But it does work to an extent for basic use cases.
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from gliner import GLiNER model = GLiNER.from_pretrained("NeuML/gliner-bert-tiny") 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"])