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zac
/
testing-lora

Image-to-Video
Diffusers
lora
template:sd-lora
ai-toolkit
Model card Files Files and versions
xet
Community

Instructions to use zac/testing-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use zac/testing-lora 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("Qwen/Qwen-Image", dtype=torch.bfloat16, device_map="cuda")
    pipe.load_lora_weights("zac/testing-lora")
    
    prompt = "John"
    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
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testing-lora
2.95 GB
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  • 1 contributor
History: 7 commits
zac's picture
zac
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  • testing.safetensors
    590 MB
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  • testing_000000500.safetensors
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  • testing_000001250.safetensors
    590 MB
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