Instructions to use DataSign/gliner-ja-pii-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use DataSign/gliner-ja-pii-v1 with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("DataSign/gliner-ja-pii-v1") 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 tokenizer.json from DataSign/gliner-ja-pii-v1: direct link, hf CLI and curl.
- Browser
- Download file 16 MB
-
https://huggingface.co/DataSign/gliner-ja-pii-v1/resolve/main/tokenizer.json
- Command line
-
hf download hf://DataSign/gliner-ja-pii-v1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/DataSign/gliner-ja-pii-v1/resolve/main/tokenizer.json
16 MB
- Xet hash:
- f0e6ae37cb3e8819ee7947b222b2a0e775ce4eaaf87ef7852ee5b3a866fbdeaa
- Size of remote file:
- 16 MB
- SHA256:
- 506beabd886b40a1fe008af4ea41be28e5a723410e5bc6ccc18850b1fea61bad
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