Token Classification
GLiNER2
Safetensors
GLiNER
English
extractor
named-entity-recognition
ner
pii
anonymisation
privacy
Eval Results (legacy)
Instructions to use OvermindLab/nerpa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER2
How to use OvermindLab/nerpa with GLiNER2:
from gliner2 import GLiNER2 model = GLiNER2.from_pretrained("OvermindLab/nerpa") # 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 OvermindLab/nerpa with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("OvermindLab/nerpa") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from OvermindLab/nerpa: direct link, hf CLI and curl.
- Browser
- Download file 8.65 MB
-
https://huggingface.co/OvermindLab/nerpa/resolve/main/tokenizer.json
- Command line
-
hf download hf://OvermindLab/nerpa/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/OvermindLab/nerpa/resolve/main/tokenizer.json
8.65 MB
File too large to display, you can check the raw version instead.