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kylinfires
/
Joy-face_change_optimized

Video-to-Video
Diffusers
English
Chinese
video-editing
streaming
quantization
int8
text-stream-stripping
Model card Files Files and versions
xet
Community

Instructions to use kylinfires/Joy-face_change_optimized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use kylinfires/Joy-face_change_optimized with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("kylinfires/Joy-face_change_optimized", dtype=torch.bfloat16, device_map="cuda")
    
    prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
    image = pipe(prompt).images[0]
  • Notebooks
  • Google Colab
  • Kaggle
Joy-face_change_optimized / training /src /models /common /diffusion
50.1 kB
Ctrl+K
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  • 1 contributor
History: 3 commits
kylinfires's picture
kylinfires
Sync main: low-VRAM live test results (624x360)
b9fc164 verified 6 days ago
  • pipelines
    Sync main: low-VRAM live test results (624x360) 6 days ago
  • schedulers
    Sync main: low-VRAM live test results (624x360) 6 days ago
  • __init__.py
    0 Bytes
    JoyAI-Video-Edit fork: int4/int8 quantization tooling, portable fused-op fallback, dark UI 7 days ago