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qf-iquest
/
EigenThink-v2

Feature Extraction
Transformers
PyTorch
bert
Model card Files Files and versions
xet
Community

Instructions to use qf-iquest/EigenThink-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use qf-iquest/EigenThink-v2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="qf-iquest/EigenThink-v2")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("qf-iquest/EigenThink-v2")
    model = AutoModel.from_pretrained("qf-iquest/EigenThink-v2", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
EigenThink-v2 / figures
1.23 kB
Ctrl+K
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  • 1 contributor
History: 1 commit
qf-iquest's picture
qf-iquest
Publish EigenThink-v2 (best checkpoint: step_1000) with full 15-benchmark model card
32534d5 verified 7 days ago
  • cover_image.png
    410 Bytes
    Publish EigenThink-v2 (best checkpoint: step_1000) with full 15-benchmark model card 7 days ago
  • eval_chart.png
    410 Bytes
    Publish EigenThink-v2 (best checkpoint: step_1000) with full 15-benchmark model card 7 days ago
  • mit_license.png
    410 Bytes
    Publish EigenThink-v2 (best checkpoint: step_1000) with full 15-benchmark model card 7 days ago