---
title: Qwen-Image-LoRA-ArtAug-v1
canonical_url: "https://www.modelscope.cn/models/DiffSynth-Studio/Qwen-Image-LoRA-ArtAug-v1"
md_url: "https://www.modelscope.cn/models/DiffSynth-Studio/Qwen-Image-LoRA-ArtAug-v1.md"
repository: DiffSynth-Studio/Qwen-Image-LoRA-ArtAug-v1
chinese_name: "Qwen-Image 美学提升 LoRA"
last_updated: 2025-11-11
license: "Apache License 2.0"
pipeline_tag: text-to-image-synthesis
tasks:
  - text-to-image-synthesis
base_model:
  - Qwen/Qwen-Image
base_model_relation: adapter
parameters: 235.9M
tensor_type:
  - F32
library_name:
  - pytorch
  - lora
  - safetensors
supports_inference: txt2img
downloads: 559
stars: 11
tags:
  - LoRA
---

# Qwen-Image-LoRA-ArtAug-v1

> Qwen-Image-LoRA-ArtAug-v1 - DiffSynth-Studio 在 ModelScope 开源的模型。Qwen-Image 美学提升 LoRA

DiffSynth-Studio/Qwen-Image-LoRA-ArtAug-v1 是 ModelScope 魔搭社区上的 235.9M 参数text-to-image-synthesis模型，采用 Apache License 2.0 许可，基于 Qwen/Qwen-Image 构建，并支持在线推理（txt2img）。

- **Repository**: DiffSynth-Studio/Qwen-Image-LoRA-ArtAug-v1
- **License**: Apache License 2.0
- **Tasks**: text-to-image-synthesis
- **Parameters**: 235.9M
- **Base model**: Qwen/Qwen-Image
- **Online inference**: txt2img
- **Tags**: LoRA
- **Downloads**: 559
- **Stars**: 11
- **Last updated**: 2025-11-11

Source: https://www.modelscope.cn/models/DiffSynth-Studio/Qwen-Image-LoRA-ArtAug-v1

---

# Qwen-Image 美学提升 LoRA

## 模型介绍

本模型是使用差分 LoRA 训练技术训练的美学提升 LoRA，沿用了与 [DiffSynth-Studio/ArtAug-lora-FLUX.1dev-v1](https://modelscope.cn/models/DiffSynth-Studio/ArtAug-lora-FLUX.1dev-v1) 类似的训练流程，训练代码基于 [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio/tree/main)，模型能够提升 [Qwen-Image](https://modelscope.cn/models/Qwen/Qwen-Image) 生成的图像美感和细节。

## 效果展示

|Qwen-Image 生成|Qwen-Image + LoRA 生成|
|-|-|
|![](./assets/image_4_base.jpg)|![](./assets/image_4_lora.jpg)|
|![](./assets/image_1_base.jpg)|![](./assets/image_1_lora.jpg)|
|![](./assets/image_0_base.jpg)|![](./assets/image_0_lora.jpg)|
|![](./assets/image_2_base.jpg)|![](./assets/image_2_lora.jpg)|
|![](./assets/image_3_base.jpg)|![](./assets/image_3_lora.jpg)|


## 推理代码

安装 [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio)：

```shell
git clone https://github.com/modelscope/DiffSynth-Studio.git  
cd DiffSynth-Studio
pip install -e .
```

推理代码：

```python
from diffsynth.pipelines.qwen_image import QwenImagePipeline, ModelConfig
import torch

pipe = QwenImagePipeline.from_pretrained(
    torch_dtype=torch.bfloat16,
    device="cuda",
    model_configs=[
        ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="transformer/diffusion_pytorch_model*.safetensors"),
        ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="text_encoder/model*.safetensors"),
        ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
    ],
    tokenizer_config=ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="tokenizer/"),
)
lora = ModelConfig(model_id="DiffSynth-Studio/Qwen-Image-LoRA-ArtAug-v1", origin_file_pattern="model.safetensors")
pipe.load_lora(pipe.dit, lora, alpha=1)
prompt = "精致肖像，水下少女，蓝裙飘逸，发丝轻扬，光影透澈，气泡环绕，面容恬静，细节精致，梦幻唯美。"
image = pipe(prompt, seed=0, num_inference_steps=40)
image.save("image.jpg")
```