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
- Downloads last month
- 1
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The HF Inference API does not support unconditional-image-generation models for diffusers library.