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:
- 014eb6ea43018ca03f3dde7bd06108f6e67a8be897007208441af06324f8c025
- Size of remote file:
- 10.7 MB
- SHA256:
- df6b9df86a4dabf8be60dd4387d98a0bdf506f03bc5e3a888d116471f0afafcc
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