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GitHub - Tencent/HunyuanDiT: Hunyuan-DiT : A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding

May 17, 2024 - github.com
The article introduces Hunyuan-DiT, a powerful multi-resolution diffusion transformer developed by Tencent, designed for fine-grained Chinese understanding. The transformer is capable of generating images from text prompts in both English and Chinese, with a particular focus on multi-turn text-to-image generation. The transformer uses a pre-trained Variational Autoencoder (VAE) to compress images into low-dimensional latent spaces and a diffusion model to learn data distribution. It also uses a Multimodal Large Language Model to refine image captions.

The article provides a detailed guide on how to use Hunyuan-DiT, including setting up the environment, downloading pretrained models, and running inference using Gradio or command line. It also provides a comparison of Hunyuan-DiT with other models, showing that it sets a new state-of-the-art in Chinese-to-image generation. The article concludes with BibTeX references for further research and a star history chart showing the popularity of the project.

Key takeaways:

  • Hunyuan-DiT is a powerful multi-resolution diffusion transformer developed by Tencent, with a fine-grained understanding of both English and Chinese.
  • The model is capable of multi-turn text-to-image generation, allowing users to create images from text prompts in a conversational manner.
  • The repository includes PyTorch model definitions, pre-trained weights, and inference/sampling code, and the developers plan to release more features and versions in the future.
  • According to professional human evaluators, Hunyuan-DiT sets a new state-of-the-art in Chinese-to-image generation compared with other open-source models.
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