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vidfom
/
lt

Diffusers
Safetensors
Model card Files Files and versions
xet
Community

Instructions to use vidfom/lt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use vidfom/lt with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("vidfom/lt", 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
lt / ltx_video /models /autoencoders
110 kB
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  • 1 contributor
History: 1 commit
vidfom's picture
vidfom
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cf0f1a5 about 1 year ago
  • __init__.py
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  • causal_conv3d.py
    1.7 kB
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  • causal_video_autoencoder.py
    44.1 kB
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  • conv_nd_factory.py
    2.18 kB
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  • dual_conv3d.py
    6.45 kB
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  • pixel_norm.py
    307 Bytes
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  • vae.py
    12.8 kB
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  • vae_encode.py
    7.06 kB
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  • video_autoencoder.py
    35.5 kB
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