Token Classification
GLiNER
PyTorch
English
entity recognition
NER
named entity recognition
zero shot
zero-shot
Instructions to use numind/NuNER_Zero-4k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use numind/NuNER_Zero-4k with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("numind/NuNER_Zero-4k") 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_long.png from numind/NuNER_Zero-4k: direct link, hf CLI and curl.
- Browser
- Download file 44 kB
-
https://huggingface.co/numind/NuNER_Zero-4k/resolve/main/zero_shot_performance_unzero_token_long.png
- Command line
-
hf download hf://numind/NuNER_Zero-4k/zero_shot_performance_unzero_token_long.png
-
curl -L -o zero_shot_performance_unzero_token_long.png https://huggingface.co/numind/NuNER_Zero-4k/resolve/main/zero_shot_performance_unzero_token_long.png
44 kB
