Stability Diffusion in Other Languages

By Rinna

From the Author:

Japanese Stable Diffusion is a Japanese-specific latent text-to-image diffusion model capable of generating photo-realistic images given any text input.

By Fengshenbang-LM

From the Author:

"我们将Noah-Wukong数据集(100M)和Zero数据集(23M)用作预训练的数据集，先用IDEA-CCNL/Taiyi-CLIP-RoBERTa-102M-ViT-L-Chinese对这两个数据集的图文对相似性进行打分，取CLIP Score大于0.2的图文对作为我们的训练集。 我们使用IDEA-CCNL/Taiyi-CLIP-RoBERTa-102M-ViT-L-Chinese作为初始化的text encoder，冻住stable-diffusion-v1-4(论文)模型的其他部分，只训练text encoder，以便保留原始模型的生成能力且实现中文概念的对齐。该模型目前在0.2亿图文对上训练了一个epoch。 我们在 32 x A100 训练了大约100小时。该版本只是一个初步的版本，我们将持续优化并开源后续模型，欢迎交流。

We use Noah-Wukong(100M) 和 Zero(23M) as our dataset, and take the image and text pairs with CLIP Score (based on IDEA-CCNL/Taiyi-CLIP-RoBERTa-102M-ViT-L-Chinese) greater than 0.2 as our Training set. We use IDEA-CCNL/Taiyi-CLIP-RoBERTa-102M-ViT-L-Chinese as our init text encoder. To keep the powerful generative capability of stable diffusion and align Chinese concepts with the images, We only train the text encoder and freeze other part of the stable-diffusion-v1-4(paper) model. It takes 100 hours to train this model based on 32 x A100. This model is a preliminary version and we will update this model continuously and open sourse. Welcome to exchange!"