Token Classification
GLiNER
PyTorch
Safetensors
English
entity recognition
NER
named entity recognition
zero shot
zero-shot
Instructions to use numind/NuNER_Zero with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use numind/NuNER_Zero with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("numind/NuNER_Zero") 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
Download zero_shot_performance_unzero_token.png from numind/NuNER_Zero: direct link, hf CLI and curl.
- Browser
- Download file 43.1 kB
-
https://huggingface.co/numind/NuNER_Zero/resolve/refs%2Fpr%2F3/zero_shot_performance_unzero_token.png
- Command line
-
hf download hf://numind/NuNER_Zero@refs/pr/3/zero_shot_performance_unzero_token.png
-
curl -L -o zero_shot_performance_unzero_token.png https://huggingface.co/numind/NuNER_Zero/resolve/refs%2Fpr%2F3/zero_shot_performance_unzero_token.png
43.1 kB
