HunyuanDiT-v1.2-Diffusers

<!-- ## **HunyuanDiT** --> <p align="center"> <img src="https://raw.githubusercontent.com/Tencent/HunyuanDiT/main/asset/logo.png" height=100> </p>

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-v1.2-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]

📈 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.

<p align="center"> <table> <thead> <tr> <th rowspan="2">Model</th> <th rowspan="2">Open Source</th> <th>Text-Image Consistency (%)</th> <th>Excluding AI Artifacts (%)</th> <th>Subject Clarity (%)</th> <th rowspan="2">Aesthetics (%)</th> <th rowspan="2">Overall (%)</th> </tr> </thead> <tbody> <tr> <td>SDXL</td> <td> ✔ </td> <td>64.3</td> <td>60.6</td> <td>91.1</td> <td>76.3</td> <td>42.7</td> </tr> <tr> <td>PixArt-α</td> <td> ✔</td> <td>68.3</td> <td>60.9</td> <td>93.2</td> <td>77.5</td> <td>45.5</td> </tr> <tr> <td>Playground 2.5</td> <td>✔</td> <td>71.9</td> <td>70.8</td> <td>94.9</td> <td>83.3</td> <td>54.3</td> </tr> <tr> <td>SD 3</td> <td>&#10008</td> <td>77.1</td> <td>69.3</td> <td>94.6</td> <td>82.5</td> <td>56.7</td> </tr> <tr> <td>MidJourney v6</td><td>&#10008</td> <td>73.5</td> <td>80.2</td> <td>93.5</td> <td>87.2</td> <td>63.3</td> </tr> <tr> <td>DALL-E 3</td><td>&#10008</td> <td>83.9</td> <td>80.3</td> <td>96.5</td> <td>89.4</td> <td>71.0</td> </tr> <tr style="font-weight: bold; background-color: #f2f2f2;"> <td>Hunyuan-DiT</td><td>✔</td> <td>74.2</td> <td>74.3</td> <td>95.4</td> <td>86.6</td> <td>59.0</td> </tr> </tbody> </table> </p>

🎥 Visualization

• Chinese Elements

<p align="center"> <img src="https://raw.githubusercontent.com/Tencent/HunyuanDiT/main/asset/chinese elements understanding.png" height=220> </p>

• Long Text Input

<p align="center"> <img src="https://raw.githubusercontent.com/Tencent/HunyuanDiT/main/asset/long text understanding.png" height=310> </p>

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