File size: 4,697 Bytes
f95af2e a2870f8 f95af2e cedfe4f f95af2e cedfe4f f95af2e cedfe4f f95af2e cedfe4f f95af2e |
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 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 |
---
pipeline_tag: any-to-any
library_name: transformers
tags:
- text-to-image
- image-editing
- image-understanding
- vision-language
- multimodal
- unified-model
- teacher-model
- diffusion
license: mit
---
## 🌌 UniPic3-Teacher-Model
<div align="center">
<img src="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-Teacher-Model** is the **high-quality teacher diffusion model** used in the UniPic 3.0 framework.
It is trained with **full multi-step diffusion sampling** and optimized for **maximum perceptual quality, semantic consistency, and realism**.
This model serves as the **teacher backbone** for:
- **Distribution Matching Distillation (DMD)**
- **Consistency / trajectory distillation**
- **Few-step student model training**
Rather than being optimized for fast inference, the teacher model prioritizes **generation fidelity and stability**, providing a strong and reliable supervision signal for downstream distilled models.
---
## 🧠 Model Characteristics
- **Role**: Teacher model (not a distilled student)
- **Sampling**: Multi-step diffusion (high-fidelity)
- **Architecture**: Unified UniPic3 Transformer
- **Tasks Supported**:
- Single-image editing
- Multi-image composition (2–6 images)
- Human–Object Interaction (HOI)
- **Resolution**: Flexible, within pixel budget constraints
- **Training Objective**:
- Flow Matching / Diffusion loss
- Used as teacher for DMD & consistency training
---
## 📊 Benchmarks
<div align="center"> <img src="unipic3_eval.png" alt="Model Teaser" width="720"> </div>
This teacher model achieves **state-of-the-art performance** on:
- Image editing benchmarks
- Multi-image composition benchmarks
It provides **high-quality supervision targets** for distilled UniPic3 student models.
---
## ⚠️ Important Note
> **This repository hosts the teacher model.**
> It is **not optimized for few-step inference**.
If you are looking for:
- ⚡ **4–8 step fast inference**
- 🚀 **Deployment-friendly distilled models**
please refer to the **UniPic3-DMD / distilled checkpoints** instead.
---
## 🧠 Usage (Teacher Model)
### 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"
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 50 \
--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 in your research, please cite:
```
@misc{wang2025skyworkunipicunifiedautoregressive,
title={Skywork UniPic: Unified Autoregressive Modeling for Visual Understanding and Generation},
author={Peiyu Wang and Yi Peng and Yimeng Gan and Liang Hu and Tianyidan Xie and Xiaokun Wang and Yichen Wei and Chuanxin Tang and Bo Zhu and Changshi Li and Hongyang Wei and Eric Li and Xuchen Song and Yang Liu and Yahui Zhou},
year={2025},
eprint={2508.03320},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2508.03320},
}
```
```
@misc{wei2025skyworkunipic20building,
title={Skywork UniPic 2.0: Building Kontext Model with Online RL for Unified Multimodal Model},
author={Hongyang Wei and Baixin Xu and Hongbo Liu and Cyrus Wu and Jie Liu and Yi Peng and Peiyu Wang and Zexiang Liu and Jingwen He and Yidan Xietian and Chuanxin Tang and Zidong Wang and Yichen Wei and Liang Hu and Boyi Jiang and William Li and Ying He and Yang Liu and Xuchen Song and Eric Li and Yahui Zhou},
year={2025},
eprint={2509.04548},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2509.04548},
}
```
|