File size: 2,820 Bytes
e8a6161 8b0fc31 6100622 e8a6161 6100622 e8a6161 6100622 7f49ef2 4e9d898 e8a6161 6100622 e8a6161 6100622 7f49ef2 e8a6161 6100622 5bde142 ce4e34c 5bde142 6100622 5bde142 6100622 5bde142 2f097f7 5bde142 6100622 ef906e7 6100622 ef906e7 6100622 a56a769 6100622 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 | ---
pipeline_tag: any-to-any
library_name: transformers
tags:
- text-to-image
- image-editing
- image-understanding
- vision-language
- multimodal
- unified-model
license: mit
---
## 🌌 Unipic3-Consistency-Model
<div align="center">
<img src="skywork-logo.png" alt="Skywork Logo" width="500">
</div>
<p align="center">
<a href="https://github.com/SkyworkAI/UniPic">
<img src="https://img.shields.io/badge/GitHub-UniPic-blue?logo=github" alt="GitHub Repo">
</a>
<a href="https://github.com/SkyworkAI/UniPic/stargazers">
<img src="https://img.shields.io/github/stars/SkyworkAI/UniPic?style=social" alt="GitHub Stars">
</a>
<a href="https://github.com/SkyworkAI/UniPic/network/members">
<img src="https://img.shields.io/github/forks/SkyworkAI/UniPic?style=social" alt="GitHub Forks">
</a>
</p>
## 📖 Introduction
<div align="center"> <img src="unipic3.png" alt="Model Teaser" width="720"> </div>
**UniPic3-Consistency-Model** is a few-step image editing and multi-image composition model based on **Consistency Flow Matching (CM)**.
The model learns a *trajectory-consistent* mapping from noisy latent states to clean images, enabling stable generation with strong structural consistency.
It is distilled from **UniPic-3** to support **fast inference (≤8 steps)** while preserving composition correctness.The model is especially suitable for scenarios requiring **geometric alignment** and **semantic coherence**, such as multi-image composition and human–object interaction (HOI).
## 📊 Benchmarks
<div align="center"> <img src="unipic3_eval.png" alt="Model Teaser" width="720"> </div>
## 🧠 Usage
### 1. Clone the Repository
```bash
git clone https://github.com/SkyworkAI/UniPic
cd UniPic-3
```
### 2. Set Up the Environment
```bash
conda create -n unipic python=3.10
conda activate unipic3
pip install -r requirements.txt
```
### 3.Batch Inference
```bash
transformer_path = "Skywork/Unipic3-Consistency-Model/ema_transformer"
python -m torch.distributed.launch --nproc_per_node=1 --master_port 29501 --use_env \
qwen_image_edit_fast/batch_inference.py \
--jsonl_path data/val.jsonl \
--output_dir work_dirs/output \
--distributed \
--num_inference_steps 8 \
--true_cfg_scale 4.0 \
--transformer transformer_path \
--skip_existing
```
## 📄 License
This model is released under the MIT License.
## Citation
If you use Skywork UniPic 3.0 in your research, please cite:
```
@article{wei2026skywork,
title={Skywork UniPic 3.0: Unified Multi-Image Composition via Sequence Modeling},
author={Wei, Hongyang and Liu, Hongbo and Wang, Zidong and Peng, Yi and Xu, Baixin and Wu, Size and Zhang, Xuying and He, Xianglong and Liu, Zexiang and Wang, Peiyu and others},
journal={arXiv preprint arXiv:2601.15664},
year={2026}
}
```
|