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:
- 21c32e84f4c6207c78307383e208b9a3b37c5f70fd75b436cdf2f85d4d0cc67a
- Size of remote file:
- 10.7 MB
- SHA256:
- 8b85e48edd9416282fece9dee3a07f462ce88e907a460ab5e874de6befd1c9f7
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