Instructions to use urchade/gliner_small-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use urchade/gliner_small-v1 with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("urchade/gliner_small-v1") 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
Commit History
-
Update README.md
Verified signature0f0f4e7
-
Update README.md
Verified signature9011131 -
Update README.md
Verified signaturef1f1fce -
better version
Verified signature9c1d330
-
fix bug
Verified signature9e6a8cb
-
Update README with installable gliner; add library_name (#1)
Verified signature- Update README with installable gliner; add library_name (c133dd0d9ef952a3937f121dc7c8c68926347a2a) Co-authored-by: Tom Aarsen <tomaarsen@users.noreply.huggingface.co>b2b2331
-
Update README.md
Verified signature172f71e
-
Update README.md
Verified signature830a779
-
Update README.md
Verified signature8c3d96e -
Push model using huggingface_hub.
Verified signaturec2f291f -
initial commit
Verified signature3fe87e2