Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with
  Fine-Grained Chinese Understanding
Authors: name: Zhimin Li, name: Jianwei Zhang, name: Qin Lin, name: Jiangfeng Xiong, name: Yanxin Long, name: Xinchi Deng, name: Yingfang Zhang, name: Xingchao Liu, name: Minbin Huang, name: Zedong Xiao, name: Dayou Chen, name: Jiajun He, name: Jiahao Li, name: Wenyue Li, name: Chen Zhang, name: Rongwei Quan, name: Jianxiang Lu, name: Jiabin Huang, name: Xiaoyan Yuan, name: Xiaoxiao Zheng, name: Yixuan Li, name: Jihong Zhang, name: Chao Zhang, name: Meng Chen, name: Jie Liu, name: Zheng Fang, name: Weiyan Wang, name: Jinbao Xue, name: Yangyu Tao, name: Jianchen Zhu, name: Kai Liu, name: Sihuan Lin, name: Yifu Sun, name: Yun Li, name: Dongdong Wang, name: Mingtao Chen, name: Zhichao Hu, name: Xiao Xiao, name: Yan Chen, name: Yuhong Liu, name: Wei Liu, name: Di Wang, name: Yong Yang, name: Jie Jiang, name: Qinglin Lu

We present Hunyuan-DiT, a text-to-image diffusion transformer with
fine-grained understanding of both English and Chinese. To construct
Hunyuan-DiT, we carefully design the transformer structure, text encoder, and
positional encoding. We also build from scratch a whole data pipeline to update
and evaluate data for iterative model optimization. For fine-grained language
understanding, we train a Multimodal Large Language Model to refine the
captions of the images. Finally, Hunyuan-DiT can perform multi-turn multimodal
dialogue with users, generating and refining images according to the context.
Through our holistic human evaluation protocol with more than 50 professional
human evaluators, Hunyuan-DiT sets a new state-of-the-art in Chinese-to-image
generation compared with other open-source models. Code and pretrained models
are publicly available at github.com/Tencent/HunyuanDiT