Instructions to use EmergentMethods/gliner_small_news-v2.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use EmergentMethods/gliner_small_news-v2.1 with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("EmergentMethods/gliner_small_news-v2.1") 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 EmergentMethods/gliner_small_news-v2.1: direct link, hf CLI and curl.
- Browser
- Download file 611 MB
-
https://huggingface.co/EmergentMethods/gliner_small_news-v2.1/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://EmergentMethods/gliner_small_news-v2.1@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/EmergentMethods/gliner_small_news-v2.1/resolve/refs%2Fpr%2F2/pytorch_model.bin
611 MB
- Xet hash:
- 156ea4aa58ab6bc9b55d154fc00e276f0c0626b6a76015a36a530d8cbbde75b0
- Size of remote file:
- 611 MB
- SHA256:
- a06130735bbee2dd303849e2bf889f2f19093090c469ce6507c7a869b8d4d322
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