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vidfom
/
Wan-T2V_14B

Diffusers
Safetensors
Model card Files Files and versions
xet
Community
1

Instructions to use vidfom/Wan-T2V_14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use vidfom/Wan-T2V_14B 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/Wan-T2V_14B", 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
Wan-T2V_14B / DiffSynth-Studio /diffsynth /processors
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  • 1 contributor
History: 1 commit
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vidfom
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9c63087 verified about 1 year ago
  • __pycache__
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  • FastBlend.py
    7.03 kB
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  • PILEditor.py
    855 Bytes
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  • RIFE.py
    3.12 kB
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  • __init__.py
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  • base.py
    118 Bytes
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  • sequencial_processor.py
    1.58 kB
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