Token Classification
GLiNER
PyTorch
English
entity recognition
NER
named entity recognition
zero shot
zero-shot
Instructions to use numind/NuNER_Zero-span with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use numind/NuNER_Zero-span with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("numind/NuNER_Zero-span") 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.md
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README.md
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NuZero span is:
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* a more powerful version of GLiNER-large-v2.1, surpassing it by **+4.5% on average**
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* is trained on the diverse
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<p align="center">
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<img src="zero_shot_performance_span.png">
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NuZero span is:
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* a more powerful version of GLiNER-large-v2.1, surpassing it by **+4.5% on average**
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* is trained on the **diverse dataset tailored for real-life use cases**
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<p align="center">
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<img src="zero_shot_performance_span.png">
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