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qnaug
/
embeddinggemma2-decision

Text Classification
Transformers
Safetensors
English
decision-model
calibration
embeddinggemma
Model card Files Files and versions
xet
Community

Instructions to use qnaug/embeddinggemma2-decision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use qnaug/embeddinggemma2-decision with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="qnaug/embeddinggemma2-decision")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("qnaug/embeddinggemma2-decision", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
embeddinggemma2-decision
1.12 GB
Ctrl+K
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  • 1 contributor
History: 2 commits
qnaug's picture
qnaug
Upload EmbeddingGemma 2 decision model
8cd99ae verified 29 days ago
  • encoder
    Upload EmbeddingGemma 2 decision model 29 days ago
  • .gitattributes
    1.58 kB
    Upload EmbeddingGemma 2 decision model 29 days ago
  • README.md
    3.43 kB
    Upload EmbeddingGemma 2 decision model 29 days ago
  • decision_model.py
    7.08 kB
    Upload EmbeddingGemma 2 decision model 29 days ago
  • head.pt
    4.73 MB
    xet
    Upload EmbeddingGemma 2 decision model 29 days ago