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A repository loosely implementing High-Resolution Image Synthesis with Latent Diffusion Models (2021) in PyTorch.

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teeny-latent-diffusion

A repository loosely implementing High-Resolution Image Synthesis with Latent Diffusion Models (2021) in PyTorch. Written for experiments surrounding permissive datasets and data augmentation. Still a work in progress.

Progress 🚧

VAE Prior 🧬

The following is a table of VAE reconstructions compared to ground truth, at 23,000 steps.

Ground Truth VAE Reconstruction at 23,000 Steps Credit
Photo by Adam Stefanca on Unsplash
Photo by Helena Lopes on Unsplash
Photo by Annie Spratt on Unsplash

Roadmap 🗺️

  • Implement a Denoiser U-Net.
  • Implement a VAE prior.
  • Implement a BERT encoder as the LDM's text encoder.
  • Create preprocessor and dataloader for Unsplash-25K.
  • Train LDM on Unsplash-25K dataset.
  • Train LDM+Bert on Unsplash-25K dataset.

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A repository loosely implementing High-Resolution Image Synthesis with Latent Diffusion Models (2021) in PyTorch.

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