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Shiroi-max
/
ddpm-mnist-conditional-32

Image-to-Image
Diffusers
TensorBoard
Safetensors
English
DDPMConditionalPipeline
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use Shiroi-max/ddpm-mnist-conditional-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use Shiroi-max/ddpm-mnist-conditional-32 with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    from diffusers.utils import load_image
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("Shiroi-max/ddpm-mnist-conditional-32", dtype=torch.bfloat16, device_map="cuda")
    
    prompt = "Turn this cat into a dog"
    input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
    
    image = pipe(image=input_image, prompt=prompt).images[0]
  • Notebooks
  • Google Colab
  • Kaggle
ddpm-mnist-conditional-32
8.07 MB
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  • 1 contributor
History: 56 commits
Shiroi-max's picture
Shiroi-max
Epoch 9
368673b almost 2 years ago
  • logs
    Epoch 9 almost 2 years ago
  • samples
    Epoch 9 almost 2 years ago
  • scheduler
    Epoch 0 almost 2 years ago
  • unet
    Epoch 9 almost 2 years ago
  • .gitattributes
    1.58 kB
    Epoch 9 almost 2 years ago
  • README.md
    101 Bytes
    Setting almost 2 years ago
  • model_index.json
    192 Bytes
    Epoch 0 almost 2 years ago
  • pipeline.py
    2.05 kB
    Setting almost 2 years ago