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obsxrver
/
Wan2.2_GTA-Style

Text-to-Video
Diffusers
wan-2.2
lora
template:sd-lora
Model card Files Files and versions
xet
Community
1

Instructions to use obsxrver/Wan2.2_GTA-Style with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use obsxrver/Wan2.2_GTA-Style with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    from diffusers.utils import export_to_video
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("Wan-AI/Wan2.2-T2V-A14B", dtype=torch.bfloat16, device_map="cuda")
    pipe.load_lora_weights("obsxrver/Wan2.2_GTA-Style")
    
    prompt = "A man with short gray hair plays a red electric guitar."
    
    output = pipe(prompt=prompt).frames[0]
    export_to_video(output, "output.mp4")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • Draw Things
Wan2.2_GTA-Style
1.84 GB
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  • 1 contributor
History: 7 commits
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obsxrver
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  • All_Checkpoints
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  • examples
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  • .gitattributes
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  • README.md
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  • WAN2.2-HighNoise_GTA-Style-v1_0.safetensors
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    xet
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  • WAN2.2-LowNoise_GTA-Style-v1_0.safetensors
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    xet
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  • config.json
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