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msh1031
/
wafer-thnn-complex-prompts

Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Model card Files Files and versions
xet
Community

Instructions to use msh1031/wafer-thnn-complex-prompts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use msh1031/wafer-thnn-complex-prompts with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("msh1031/wafer-thnn-complex-prompts", dtype=torch.bfloat16, device_map="cuda")
    
    prompt = "a pha photo of image of wafer defect captured through a Scanning Electron Microscope, a defect should be repeatedly formed in a single or multiple lines in the shape of a horse's hoop"
    image = pipe(prompt).images[0]
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • Draw Things
  • DiffusionBee
wafer-thnn-complex-prompts / vae
335 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
msh1031's picture
msh1031
End of training
5223f65 almost 3 years ago
  • config.json
    751 Bytes
    End of training almost 3 years ago
  • diffusion_pytorch_model.safetensors
    335 MB
    xet
    End of training almost 3 years ago