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lightx2v
/
Wan2.1-T2V-14B-StepDistill-CfgDistill-Lightx2v

Image-to-Video
Diffusers
Safetensors
English
Chinese
t2v
video generation
Model card Files Files and versions
xet
Community
8

Instructions to use lightx2v/Wan2.1-T2V-14B-StepDistill-CfgDistill-Lightx2v with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use lightx2v/Wan2.1-T2V-14B-StepDistill-CfgDistill-Lightx2v 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("lightx2v/Wan2.1-T2V-14B-StepDistill-CfgDistill-Lightx2v", 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")
  • Notebooks
  • Google Colab
  • Kaggle
Wan2.1-T2V-14B-StepDistill-CfgDistill-Lightx2v
85.7 GB
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