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whr778
/
gliner2-base-v1-casie

Token Classification
GLiNER2
Safetensors
English
extractor
information-extraction
named-entity-recognition
relation-extraction
event-extraction
text-classification
Model card Files Files and versions
xet
Community

Instructions to use whr778/gliner2-base-v1-casie with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • GLiNER2

    How to use whr778/gliner2-base-v1-casie with GLiNER2:

    from gliner2 import GLiNER2
    
    model = GLiNER2.from_pretrained("whr778/gliner2-base-v1-casie")
    
    # 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-base-v1-casie
842 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
whr778's picture
whr778
Add model card as README
121440b verified 6 days ago
  • encoder_config
    Upload GLiNER2 event checkpoint 6 days ago
  • .gitattributes
    1.52 kB
    initial commit 6 days ago
  • README.md
    4.1 kB
    Add model card as README 6 days ago
  • config.json
    505 Bytes
    Upload GLiNER2 event checkpoint 6 days ago
  • eval_metrics.json
    30.6 kB
    Upload GLiNER2 event checkpoint 6 days ago
  • model.safetensors
    834 MB
    xet
    Upload GLiNER2 event checkpoint 6 days ago
  • test_metrics.json
    30.3 kB
    Upload GLiNER2 event checkpoint 6 days ago
  • tokenizer.json
    8.33 MB
    Upload GLiNER2 event checkpoint 6 days ago
  • tokenizer_config.json
    722 Bytes
    Upload GLiNER2 event checkpoint 6 days ago