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
File size: 349 Bytes
d541f20 d64a54e d541f20 d64a54e d541f20 d64a54e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"max_width": 8,
"special_tokens": {
"[P]": 250104,
"[E]": 250106,
"[L]": 250108,
"[SEP_TEXT]": 250103
},
"onnx_files": {
"quantized": {
"encoder": "encoder_int8_int4.onnx",
"classifier": "classifier_int8.onnx",
"span_rep": "span_rep_int8.onnx",
"count_embed": "count_lstm_int8.onnx"
}
}
}
|