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
| { | |
| "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" | |
| } | |
| } | |
| } | |