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vidfom
/
Wav2

Diffusers
Safetensors
Model card Files Files and versions
xet
Community

Instructions to use vidfom/Wav2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use vidfom/Wav2 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/Wav2", 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
Wav2 / diffsynth /prompters
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  • 2 contributors
History: 1 commit
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vidfom
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  • __pycache__
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  • __init__.py
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  • base_prompter.py
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  • cog_prompter.py
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  • flux_prompter.py
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  • hunyuan_dit_prompter.py
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  • hunyuan_video_prompter.py
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  • kolors_prompter.py
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  • omnigen_prompter.py
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  • omost.py
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  • prompt_refiners.py
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  • sd3_prompter.py
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