DiffEnc-8-2 trained on CIFAR-10

Checkpoints for an image generation model trained on CIFAR-10.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 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 of size 2. That is the diffusion model uses 8 "down-blocks" in the U-net. See details in article.Random seeds: 1, 2, 13, 42, 70

本数据集包含在 CIFAR-10 数据集上训练的图像生成模型的检查点。该模型采用 Jax 编写。有关加载检查点的代码，请参阅 GitHub 仓库。模型为变分扩散模型（VDM，https://arxiv.org/abs/2107.00630），并额外添加了一个可训练的时间相关编码器，用于《DiffEnc：具有学习编码器的变分扩散》一文（https://arxiv.org/abs/2310.19789）。模型采用 v 参数化进行损失计算。扩散模型规模为 8，编码器规模为 2，即扩散模型在 U-net 中使用了 8 个“下采样块”。详情请参阅相关论文。随机种子：1, 2, 13, 42, 70。