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fastino
/
GLiNER2.5-Decide-1B

Token Classification
GLiNER2
Safetensors
English
extractor
Text classification
Intent classification
Sentiment Analysis
Topic classification
Named Entity Recognition
Model card Files Files and versions
xet
Community

Instructions to use fastino/GLiNER2.5-Decide-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • GLiNER2

    How to use fastino/GLiNER2.5-Decide-1B with GLiNER2:

    from gliner2 import GLiNER2
    
    model = GLiNER2.from_pretrained("fastino/GLiNER2.5-Decide-1B")
    
    # 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-Decide-1B
4.76 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
urchade's picture
urchade
Point the fine-tune button to agent.fastino.ai
688cd7b verified 2 days ago
  • encoder_config
    Upload GLiNER2.5-Decide-1B at step 285000 5 days ago
  • .gitattributes
    1.59 kB
    Upload GLiNER2.5-Decide-1B at step 285000 5 days ago
  • GLiNER-2.5-Decision-HF-Banner.png
    648 kB
    xet
    Upload GLiNER2.5-Decide-1B at step 285000 5 days ago
  • README.md
    17 kB
    Point the fine-tune button to agent.fastino.ai 2 days ago
  • config.json
    464 Bytes
    Upload GLiNER2.5-Decide-1B at step 285000 5 days ago
  • model.safetensors
    4.76 GB
    xet
    Upload GLiNER2.5-Decide-1B at step 285000 5 days ago
  • tokenizer.json
    3.59 MB
    Upload GLiNER2.5-Decide-1B at step 285000 5 days ago
  • tokenizer_config.json
    559 Bytes
    Upload GLiNER2.5-Decide-1B at step 285000 5 days ago