Token Classification
GLiNER
PyTorch
English
NER
GLiNER
information extraction
encoder
entity recognition
modernbert
bi-encoder
scalable-ner
zero-shot-ner
Instructions to use knowledgator/gliner-bi-base-v2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use knowledgator/gliner-bi-base-v2.0 with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("knowledgator/gliner-bi-base-v2.0") 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
Adding `safetensors` variant of this model
#3 opened 4 months ago
by
SFconvertbot
Adding `safetensors` variant of this model
#2 opened 7 months ago
by
SFconvertbot
Adding `safetensors` variant of this model
#1 opened about 1 year ago
by
SFconvertbot