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 pytorch_model.bin from numind/NuNER_Zero: direct link, hf CLI and curl.
- Browser
- Download file 1.8 GB
-
https://huggingface.co/numind/NuNER_Zero/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://numind/NuNER_Zero/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/numind/NuNER_Zero/resolve/main/pytorch_model.bin
1.8 GB
- Xet hash:
- 4791877706b28cdc8429d9dca04a88cb88c13b01969196441666e4c331675158
- Size of remote file:
- 1.8 GB
- SHA256:
- 96a89110ff7d5d029a1b1bc1236dc46b9e01202ca807a8d319fd4fe3009403f5
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