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finetrainers
/
Wan2.1-I2V-14B-480P-3dgs-v0

Image-to-Video
Diffusers
text-to-video
diffusers-training
template:sd-lora
wan
Model card Files Files and versions
xet
Community

Instructions to use finetrainers/Wan2.1-I2V-14B-480P-3dgs-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use finetrainers/Wan2.1-I2V-14B-480P-3dgs-v0 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("finetrainers/Wan2.1-I2V-14B-480P-3dgs-v0", dtype=torch.bfloat16, device_map="cuda")
    pipe.to("cuda")
    
    prompt = "3DGS_DISSOLVE A vibrant green Mustang GT parked in a parking lot. The car is positioned at an angle, showcasing its sleek design and black rims. The car's hood is black, contrasting with the green body. The car gradually transforms and bursts into red sparks, creating a dramatic and dynamic visual effect against a dark backdrop."
    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")
  • Notebooks
  • Google Colab
  • Kaggle
Wan2.1-I2V-14B-480P-3dgs-v0
218 MB
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  • 1 contributor
History: 4 commits
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a-r-r-o-w
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