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Remade-AI
/
Crane-down

Image-to-Video
Diffusers
English
text-to-image
lora
template:diffusion-lora
Model card Files Files and versions
xet
Community

Instructions to use Remade-AI/Crane-down with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use Remade-AI/Crane-down 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("Wan-AI/Wan2.1-I2V-14B-480P,Wan-AI/Wan2.1-I2V-14B-480P-Diffusers", dtype=torch.bfloat16, device_map="cuda")
    pipe.load_lora_weights("Remade-AI/Crane-down")
    
    prompt = "The video shows an elderly man with a long white beard, glasses, and a work shirt working on radios on a wooden table in a workshop filled with vintage radios. The man is concentrating on fixing a radio. The cr4n3 crane down camera motion begins high, looking over the man's shoulder, slowly lowering the view to show him repairing the radio more closely, focusing on his hands. The camera continues to move downwards, getting closer to the radios on the table."
    input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png")
    
    image = pipe(image=input_image, prompt=prompt).frames[0]
    export_to_video(output, "output.mp4")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • Draw Things
Crane-down
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  • 1 contributor
History: 6 commits
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Remade
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  • README.md
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  • crane_down.safetensors
    359 MB
    xet
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