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Video-Reason
/
VBVR-Pro-BAGEL

Image-to-Image
Transformers
Safetensors
bagel
image-editing
image-generation
interleaved-generation
vbvr-pro
Model card Files Files and versions
xet
Community

Instructions to use Video-Reason/VBVR-Pro-BAGEL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Video-Reason/VBVR-Pro-BAGEL with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-to-image", model="Video-Reason/VBVR-Pro-BAGEL")
    # Load model directly
    from transformers import Bagel
    model = Bagel.from_pretrained("Video-Reason/VBVR-Pro-BAGEL", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
VBVR-Pro-BAGEL
29.6 GB
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  • 1 contributor
History: 2 commits
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wruisi
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  • .gitattributes
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  • README.md
    25 kB
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  • ae.safetensors
    335 MB
    xet
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  • config.json
    1.5 kB
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  • generation_config.json
    243 Bytes
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  • llm_config.json
    663 Bytes
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  • merges.txt
    1.67 MB
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  • model.safetensors
    29.2 GB
    xet
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  • model.safetensors.index.json
    120 kB
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  • preprocessor_config.json
    393 Bytes
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  • tokenizer.json
    7.03 MB
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  • tokenizer_config.json
    7.31 kB
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  • vit_config.json
    205 Bytes
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  • vocab.json
    2.78 MB
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