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:
- 6b4281e772004a0bb297bc3a0c5f4c235209137f1a3460369618337d218a47aa
- Size of remote file:
- 1.23 MB
- SHA256:
- 27739ae6faaf3048f8aacfad391939517be8e1a48198ccc1bd1413b71bc50ea6
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