urchade/pubmed-ner-mistral-v0.1
Updated • 49 • 1
How to use GooKSL/gliner_large_bio-v0.1 with GLiNER:
from gliner import GLiNER
model = GLiNER.from_pretrained("GooKSL/gliner_large_bio-v0.1")
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"])This version is trained with "urchade/pubmed-ner-mistral-v0.1" which is commercially permissible.
This version can work for many domains, but better than other GLiNER models in the biomedical domain. Use with threshold=0.3 for better performance.