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:
- 82e23549cdf4f6ea5eff12644d3fd0135305e463121f3deac158291db47ad6f1
- Size of remote file:
- 16.6 MB
- SHA256:
- d22b0031b2ff0d02b0d20010f8b23f625d900c11d855efc40ed696b6e4e9c715
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