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Hunyuan-DiT : A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding

混元-DiT: 具有细粒度中文理解的多分辨率Diffusion Transformer

[Arxiv] [project page] [github]

This repo contains the pre-trained text-to-image model in 🤗 Diffusers format.

Dependency

Please install PyTorch first, following the instruction in https://pytorch.org

Install the latest version of transformers with pip:

pip install --upgrade transformers

Then install the latest github version of 🤗 Diffusers with pip:

pip install git+https://github.com/huggingface/diffusers.git

Example Usage with 🤗 Diffusers

import torch
from diffusers import HunyuanDiTPipeline

pipe = HunyuanDiTPipeline.from_pretrained("Tencent-Hunyuan/HunyuanDiT-v1.1-Diffusers", torch_dtype=torch.float16)
pipe.to("cuda")

# You may also use English prompt as HunyuanDiT supports both English and Chinese
# prompt = "An astronaut riding a horse"
prompt = "一个宇航员在骑马"
image = pipe(prompt).images[0]

image/png

📈 Comparisons

In order to comprehensively compare the generation capabilities of HunyuanDiT and other models, we constructed a 4-dimensional test set, including Text-Image Consistency, Excluding AI Artifacts, Subject Clarity, Aesthetic. More than 50 professional evaluators performs the evaluation.

Model Open Source Text-Image Consistency (%) Excluding AI Artifacts (%) Subject Clarity (%) Aesthetics (%) Overall (%)
SDXL 64.3 60.6 91.1 76.3 42.7
PixArt-α 68.3 60.9 93.2 77.5 45.5
Playground 2.5 71.9 70.8 94.9 83.3 54.3
SD 3 77.1 69.3 94.6 82.5 56.7
MidJourney v6 73.5 80.2 93.5 87.2 63.3
DALL-E 3 83.9 80.3 96.5 89.4 71.0
Hunyuan-DiT 74.2 74.3 95.4 86.6 59.0

🎥 Visualization

  • Chinese Elements

  • Long Text Input

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