urchade/synthetic-pii-ner-mistral-v1
Updated โข 241 โข 19
How to use NeuML/gliner-bert-tiny with GLiNER:
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"])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.