Instructions to use nicolasembleton/gliner2.5-multi-v1-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER2
How to use nicolasembleton/gliner2.5-multi-v1-onnx with GLiNER2:
from gliner2 import GLiNER2 model = GLiNER2.from_pretrained("nicolasembleton/gliner2.5-multi-v1-onnx") # Extract entities text = "Apple CEO Tim Cook announced iPhone 15 in Cupertino yesterday." result = extractor.extract_entities(text, ["company", "person", "product", "location"]) print(result) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57acd15dcb5b449069fabb37c13416d54a784a7d1d2510e5af79ee5a7aed351c
- Size of remote file:
- 7.38 MB
- SHA256:
- ef85db425fe9827cc9e89e586cb05959c2542264b733409c1d0fee2e84b60b5b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.