MeinaHentai is a checkpoint model for stable diffusion that can be used for a variety of tasks, including image generation, image translation, and style transfer. It is based on the diffusion model proposed by Chen et al. (2023), but it uses a checkpointing mechanism to improve stability and performance.
The checkpointing mechanism works by saving the model state at regular intervals during training. This allows the model to be restored to a previous state if it diverges during training. The checkpointing mechanism also allows the model to be trained for longer periods of time without becoming unstable.
MeinaHentai is available as an open-source library. It can be used with a variety of image datasets, including CIFAR-10, ImageNet, and CelebA.
