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fastino
/
gliner2-multi-v1

GLiNER2
Safetensors
extractor
Token Classification
Zero-Shot Classification
Text Classification
relation extraction
Structured extraction
Model card Files Files and versions
xet
Community
6

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

  • Libraries
  • GLiNER2

    How to use fastino/gliner2-multi-v1 with GLiNER2:

    from gliner2 import GLiNER2
    
    model = GLiNER2.from_pretrained("fastino/gliner2-multi-v1")
    
    # 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-multi-v1
1.25 GB
Ctrl+K
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  • 2 contributors
History: 8 commits
urchade's picture
urchade
Update README.md
cc151f5 verified about 1 month ago
  • encoder_config
    Upload GLiNER2 6 months ago
  • image
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  • .gitattributes
    1.62 kB
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  • README.md
    5.42 kB
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  • added_tokens.json
    230 Bytes
    Upload GLiNER2 6 months ago
  • config.json
    234 Bytes
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  • model.safetensors
    1.23 GB
    xet
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  • special_tokens_map.json
    2.41 kB
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  • spm.model
    4.31 MB
    xet
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  • tokenizer.json
    16.3 MB
    xet
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  • tokenizer_config.json
    21.6 kB
    Upload GLiNER2 6 months ago