Token Classification
GLiNER
ONNX
German
English
extractor
ner
zero-shot
pii-detection
privacy
multilingual
quantized
edge
Instructions to use patronus-studio/gliner2-multi-edge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use patronus-studio/gliner2-multi-edge with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("patronus-studio/gliner2-multi-edge") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97321606a45168e11dc8b3ee6c4694b3f5aafd47160f265af810937856e6ffaf
- Size of remote file:
- 1.23 MB
- SHA256:
- 758592271c097844b4f8ad1736c258d3b3ae36ed6ee482eb579a0fca9ae2b765
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