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:
- 8b7a6d4e8b2e0784ba7cc1146c052b7f9b1f052fdbbb6676e72d738110b5da2a
- Size of remote file:
- 16.6 MB
- SHA256:
- a509475d60f41ea4615451db5223c38aee793004d008785794bbadae878ac259
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