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IPostYellow
/
TurboWan2.2-I2V-A14B-INT8-Diffusers

Image-to-Video
Diffusers
Safetensors
Wan2.2
WanImageToVideoDmdPipeline
diffusion
video-generation
turbodiffusion
Model card Files Files and versions
xet
Community

Instructions to use IPostYellow/TurboWan2.2-I2V-A14B-INT8-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use IPostYellow/TurboWan2.2-I2V-A14B-INT8-Diffusers with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    from diffusers.utils import load_image, export_to_video
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("IPostYellow/TurboWan2.2-I2V-A14B-INT8-Diffusers", dtype=torch.bfloat16, device_map="cuda")
    pipe.to("cuda")
    
    prompt = "A man with short gray hair plays a red electric guitar."
    image = load_image(
        "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png"
    )
    
    output = pipe(image=image, prompt=prompt).frames[0]
    export_to_video(output, "output.mp4")
  • Wan2.2

    How to use IPostYellow/TurboWan2.2-I2V-A14B-INT8-Diffusers with Wan2.2:

    # No code snippets available yet for this library.
    
    # To use this model, check the repository files and the library's documentation.
    
    # Want to help? PRs adding snippets are welcome at:
    # https://github.com/huggingface/huggingface.js
  • Notebooks
  • Google Colab
  • Kaggle
TurboWan2.2-I2V-A14B-INT8-Diffusers / text_encoder
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  • 1 contributor
History: 1 commit
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IPostYellow
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  • config.json
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  • model-00001-of-00003.safetensors
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  • model-00002-of-00003.safetensors
    4.93 GB
    xet
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  • model-00003-of-00003.safetensors
    3.46 GB
    xet
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  • model.safetensors.index.json
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