Model Card for Unit 1 of the Diffusion Models Class 🧨
This model is a diffusion model for unconditional image generation of black-and-white images of handwritten digits. The number of cycles of the training loop is 10. Learning rate is 4e-4. This model has a good generation effect.
Usage
from diffusers import DDPMPipeline
pipeline = DDPMPipeline.from_pretrained('BackTo2014/mnist-demo3')
image = pipeline().images[0]
image
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This model is not currently available via any of the supported third-party Inference Providers, and
the HF Inference API does not support diffusers models with pipeline type unconditional-image-generation