Instructions to use DeepMount00/universal_ner_ita with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use DeepMount00/universal_ner_ita with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("DeepMount00/universal_ner_ita") 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"]) - Notebooks
- Google Colab
- Kaggle
Update README with installable gliner; add library_name
#1
by tomaarsen HF Staff - opened
Hello!
Pull Request overview
- Update README with installable gliner
- Add
library_name: gliner. This will eventually add a "Use in GLiNER" model in the top right on Hugging Face
Details
gliner was just added to PyPI, making this model much easier to use! https://pypi.org/project/gliner/
- Tom Aarsen
DeepMount00 changed pull request status to merged