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ByteDance
/
Bernini-R-Diffusers

Image-Text-to-Video
Diffusers
Safetensors
bernini_renderer
Model card Files Files and versions
xet
Community

Instructions to use ByteDance/Bernini-R-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use ByteDance/Bernini-R-Diffusers with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("ByteDance/Bernini-R-Diffusers", dtype=torch.bfloat16, device_map="cuda")
    
    prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
    image = pipe(prompt).images[0]
  • Notebooks
  • Google Colab
  • Kaggle
Bernini-R-Diffusers
126 GB
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  • 1 contributor
History: 5 commits
SsyzeChen's picture
SsyzeChen
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  • scheduler
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  • text_encoder
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  • tokenizer
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  • transformer
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  • transformer_2
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  • vae
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  • .gitattributes
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  • README.md
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  • config.json
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