DiffEnc-8-nt trained on MNIST

Checkpoints for an image generation model trained on MNIST.
The model was made in Jax. See the github repository for code to load the checkpoints.
The model is a variational diffusion model (VDM, https://arxiv.org/abs/2107.00630) with an added non-trainable time-dependent encoder trained for the article "DiffEnc: Variational Diffusion with a Learned Encoder" (https://arxiv.org/abs/2310.19789).
Model uses v-parametrization for the loss. The diffusion model is of size 8 and the encoder is non-trainable. That is, the diffusion model uses 8 "down-blocks" in the U-net. See details in article.
Model was trained on MNIST for 2 million steps with a batch size of 128.
Random seeds: 1, 2, 13, 42, 70