
# WQ-HD

## 模型介绍

本模型依托魔搭社区（ModelScope）AIGC专区[模型训练](https://modelscope.cn/aigc/modelTraining)环境与算力完成训练。

* 模型类型：LoRA
* 基础模型：[HiDream-ai/HiDream-O1-Image](https://modelscope.cn/models/HiDream-ai/HiDream-O1-Image)
* 训练代码：[DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio)
* 训练数据量：300
* 总训练步数：10000
* 开源协议：Apache-2.0

## 推理代码

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

```bash
pip install diffsynth
```

开始推理：

```python
from diffsynth.pipelines.hidream_o1_image import HiDreamO1ImagePipeline, ModelConfig
import torch

pipe = HiDreamO1ImagePipeline.from_pretrained(
    torch_dtype=torch.bfloat16,
    device="cuda",
    model_configs=[
        ModelConfig(model_id="HiDream-ai/HiDream-O1-Image", origin_file_pattern="*.safetensors"),
    ],
    processor_config=ModelConfig(model_id="HiDream-ai/HiDream-O1-Image"),
)
pipe.load_lora(pipe.dit, ModelConfig(model_id="Devilworld/WQ-HD", origin_file_pattern="WQ-HD_c1-st10000.safetensors"))
prompt = "a cat"
image = pipe(prompt=prompt, num_inference_steps=30, cfg_scale=4)
image.save("image.jpg")
```


Devilworld/WQ-HD

WQ-HD_c1-st3000.safetensors

c1-st3000

c1-st10000

c1-st9000

c1-st8000

c1-st7000

c1-st6000

c1-st5000

c1-st4000

c1-st2000

c1-st1000

Files with SHA256: be9fbdfb73de5cb18383e5da4aa0ac20a033f8a2a98c88cb476b2ed0d95f832a