Token Classification
GLiNER2
ONNX
GLiNER
Rust
pii
ner
privacy
redaction
information-extraction
span-extraction
iobinding
Instructions to use SemplificaAI/gliner2-privacy-filter-PII-multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER2
How to use SemplificaAI/gliner2-privacy-filter-PII-multi with GLiNER2:
from gliner2 import GLiNER2 model = GLiNER2.from_pretrained("SemplificaAI/gliner2-privacy-filter-PII-multi") # Extract entities text = "Apple CEO Tim Cook announced iPhone 15 in Cupertino yesterday." result = extractor.extract_entities(text, ["company", "person", "product", "location"]) print(result) - GLiNER
How to use SemplificaAI/gliner2-privacy-filter-PII-multi with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("SemplificaAI/gliner2-privacy-filter-PII-multi") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
Initial commit β ONNX 8-fragment export (FP32 + FP16 + FP16_IOBinding) of fastino/gliner2-privacy-filter-PII-multi
a255827 verified - 1.62 kB
- 7.29 kB
- 2.37 MB xet
- 2.37 MB xet
- 4.73 MB xet
- 21.3 MB xet
- 21.3 MB xet
- 42.6 MB xet
- 2.43 MB xet
- 2.42 MB xet
- 4.85 MB xet
- 556 MB xet
- 556 MB xet
- 1.11 GB xet
- 2.15 kB xet
- 1.74 kB xet
- 1.33 kB xet
- 5.88 kB xet
- 5.45 kB xet
- 3.83 kB xet
- 33.1 MB xet
- 33.1 MB xet
- 66.1 MB xet
- 524 Bytes xet
- 252 Bytes xet
- 252 Bytes xet
- 16 MB xet