DiffEnc-32-4 trained on CIFAR-10

<p dir="ltr">Checkpoints for an image generation model trained on CIFAR-10.</p><p dir="ltr">The model was made in Jax. See the github repository for code to load the checkpoints.</p><p dir="ltr">The model is a variational diffusion model (VDM, https://arxiv.org/abs/2107.00630) with an added trainable time-dependent encoder trained for the article "DiffEnc: Variational Diffusion with a Learned Encoder" (https://arxiv.org/abs/2310.19789).</p><p dir="ltr">Model uses v-parametrization for the loss. The diffusion model is of size 32 and the encoder is of size 4. That is, the diffusion model uses 32 "down-blocks" in the U-net. See details in article.</p><p dir="ltr">Model was trained on CIFAR-10 for 8 million steps.</p><p dir="ltr">Random seeds: 1, 2, 13</p><p><br></p>