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tangjs
/
uv-lora

Text-to-Image
Diffusers
TensorBoard
stable-diffusion
stable-diffusion-diffusers
lora
Model card Files Files and versions
xet
Metrics Training metrics Community

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

  • Libraries
  • Diffusers

    How to use tangjs/uv-lora with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("SG161222/Realistic_Vision_V5.1_noVAE", dtype=torch.bfloat16, device_map="cuda")
    pipe.load_lora_weights("tangjs/uv-lora")
    
    prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
    image = pipe(prompt).images[0]
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • Draw Things
  • DiffusionBee
uv-lora / logs
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  • 1 contributor
History: 2 commits
tangjs's picture
tangjs
End of training
a1e5a8c over 2 years ago
  • text2image-fine-tune
    End of training over 2 years ago