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prodevroger
/
tryait

Image-to-Image
Diffusers
ONNX
Safetensors
StableDiffusionXLInpaintPipeline
Model card Files Files and versions
xet
Community

Instructions to use prodevroger/tryait with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use prodevroger/tryait with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import AutoPipelineForInpainting
    from diffusers.utils import load_image
    
    # switch to "mps" for apple devices
    pipe = AutoPipelineForInpainting.from_pretrained("prodevroger/tryait", dtype=torch.float16, device_map="cuda")
    
    img_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png"
    mask_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png"
    
    image = load_image(img_url).resize((1024, 1024))
    mask_image = load_image(mask_url).resize((1024, 1024))
    
    prompt = "a tiger sitting on a park bench"
    generator = torch.Generator(device="cuda").manual_seed(0)
    
    image = pipe(
      prompt=prompt,
      image=image,
      mask_image=mask_image,
      guidance_scale=8.0,
      num_inference_steps=20,  # steps between 15 and 30 work well for us
      strength=0.99,  # make sure to use `strength` below 1.0
      generator=generator,
    ).images[0]
  • Notebooks
  • Google Colab
  • Kaggle
tryait
29.4 GB
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  • 2 contributors
History: 6 commits
prodevroger's picture
prodevroger
Delete README.md
15a6684 verified about 2 years ago
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  • tokenizer
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  • vae
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  • .gitattributes
    1.63 kB
    TryAIt model Deployment about 2 years ago
  • model_index.json
    750 Bytes
    TryAIt model Deployment about 2 years ago