# 偶映-suiyuan4-krea2-turbo
## 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：[krea/Krea-2-Turbo](https://modelscope.cn/models/krea/Krea-2-Turbo)
* 训练代码：[DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio)
* 训练数据量：98
* 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.krea2 import Krea2Pipeline, ModelConfig
import torch
pipe = Krea2Pipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[
ModelConfig(model_id="krea/Krea-2-Turbo", origin_file_pattern="turbo.safetensors"),
ModelConfig(model_id="Qwen/Qwen3-VL-4B-Instruct", origin_file_pattern="*.safetensors"),
ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
],
tokenizer_config=ModelConfig(model_id="Qwen/Qwen3-VL-4B-Instruct", origin_file_pattern=""),
)
pipe.load_lora(pipe.dit, ModelConfig(model_id="orangeHong/allin-suiyuan5-krea2-turbo", origin_file_pattern="allin-suiyuan5-krea2-turbo_c1-st10000.safetensors"))
prompt = "a cat"
image = pipe(
prompt, seed=0,
num_inference_steps=8, cfg_scale=1, mu=1.15,
)
image.save("image.jpg")
```