Instructions to use NORMA-DEV/Gliner_haystack with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use NORMA-DEV/Gliner_haystack with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("NORMA-DEV/Gliner_haystack") 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 NORMA-DEV/Gliner_haystack: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/NORMA-DEV/Gliner_haystack/resolve/main/tokenizer.json
- Command line
-
hf download hf://NORMA-DEV/Gliner_haystack/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/NORMA-DEV/Gliner_haystack/resolve/main/tokenizer.json
711 kB
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