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nicolasembleton
/
gliner2.5-multi-v1-onnx

Token Classification
ONNX
GLiNER2
gliner2.5
boundary
webgpu
text-classification
relation-extraction
Model card Files Files and versions
xet
Community

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
gliner2.5-multi-v1-onnx / onnx
Ctrl+K
Ctrl+K
  • 1 contributor
History: 7 commits
nicolasembleton's picture
nicolasembleton
add attrs.onnx: dynamo score_explicit_spans (pad 512/8/16)
3fb2f85 verified about 22 hours ago
  • attrs.onnx
    7.38 MB
    xet
    add attrs.onnx: dynamo score_explicit_spans (pad 512/8/16) about 22 hours ago
  • heads.onnx
    23.7 MB
    xet
    v4 export: [R] role gather + heads.onnx relation scorer 1 day ago
  • model.onnx
    1.12 GB
    xet
    v5 export: candidate_states + records.onnx assignment head 1 day ago
  • records.onnx
    1.19 MB
    xet
    v5 export: candidate_states + records.onnx assignment head 1 day ago