Instructions to use urchade/gliner_large-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use urchade/gliner_large-v1 with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("urchade/gliner_large-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 pytorch_model.bin from urchade/gliner_large-v1: direct link, hf CLI and curl.
- Browser
- Download file 1.78 GB
-
https://huggingface.co/urchade/gliner_large-v1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://urchade/gliner_large-v1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/urchade/gliner_large-v1/resolve/main/pytorch_model.bin
1.78 GB
- Xet hash:
- 6be569049f863f5ced2156a415800b68bf0efa6b062d1ec9adc71f014a50fe99
- Size of remote file:
- 1.78 GB
- SHA256:
- fb99fe1f8687f932b5ff4ad500b50eabb38bbbcad0b9f922a01979580aaa0086
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