Instructions to use vicgalle/gliner-small-pii with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use vicgalle/gliner-small-pii with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("vicgalle/gliner-small-pii") text = "Cristiano Ronaldo dos Santos Aveiro was born on 5 February 1985 in Funchal, Madeira, Portugal." labels = ["person", "date", "location"] entities = model.predict_entities(text, labels) for entity in entities: print(entity["text"], "=>", entity["label"]) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from vicgalle/gliner-small-pii: direct link, hf CLI and curl.
- Browser
- Download file 664 MB
-
https://huggingface.co/vicgalle/gliner-small-pii/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://vicgalle/gliner-small-pii/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/vicgalle/gliner-small-pii/resolve/main/pytorch_model.bin
664 MB
- Xet hash:
- ebab3ed58721d882f210019a7e04c0b733f0d0071e47b88bf975102a88b79005
- Size of remote file:
- 664 MB
- SHA256:
- 0a62c3af9a59ea93a22de7c132f7e09774e062c0f3cdac005c885bb91d1566fc
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