Instructions to use rafmacalaba/gliner-probe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use rafmacalaba/gliner-probe with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("rafmacalaba/gliner-probe") 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 rafmacalaba/gliner-probe: direct link, hf CLI and curl.
- Browser
- Download file 1.78 GB
-
https://huggingface.co/rafmacalaba/gliner-probe/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://rafmacalaba/gliner-probe/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/rafmacalaba/gliner-probe/resolve/main/pytorch_model.bin
1.78 GB
- Xet hash:
- a88f249b45f20bac2935cc3488b433add823aa98d8532ca47cc9add52632eb80
- Size of remote file:
- 1.78 GB
- SHA256:
- a14726bd95a24083bea8eef757831ebc520fe3a2278c0c7b54662c08ecffd839
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