<h1 id="lei-nano-or-bear-daddy-or">lei nano | bear daddy |熊叔写真</h1><h3 id="critical-warning-or">🔴 CRITICAL WARNING | 重要警告</h3><p><strong>Please load the specific workflow template for your version.</strong> <strong>请务必加载对应的 ComfyUI 工作流模板。</strong></p><hr /><h3 id="model-overview-or">⚡ Model Overview | 模型简介</h3><h3 id="english-this-model-is-a-lora-specialized-in-generating-photorealistic-stout-east-asian-&quot;bear-daddies&quot;."><strong>[English]</strong> This model is a LoRA specialized in generating photorealistic, stout East Asian "Bear Daddies".</h3><ul><li><p>(Trigger: <code>lei nano</code>)</p></li></ul><h3 id="lora&quot;&quot;"><strong>[中文]</strong> 这是一个专用的 LoRA，专注于生成超写实风格、壮硕体型的东方“熊叔/大叔”。</h3><ul><li><p><strong>理想复现：</strong> 针对“壮硕大叔”体型微调——结实厚重、成熟稳重，带有湖南特有的粗犷气质。</p></li><li><p>触发词 ：<code>lei nano</code></p></li></ul><p><code>触发词可能有变化，使用文件名里的作为触发词，这一般是正确的，我的lora命名规则是 模型名+触发词，例如 </code><strong><em>Zimageturbo-tangNano Zimage Turbo 是模型名，tangNano是触发词。</em></strong></p><hr /><h3></h3><p></p>

lei nano | bear daddy |熊叔写真

ZimageTurbo-leiNano_c1-st4000.safetensors

v1.0 (ZImageTurbo)

v1.0（Z image Base ZIB）


# 

## Model Introduction

This model is trained using the [Civision/model training](https://modelscope.ai/civision/modelTraining) environment and computing resources provided by ModelScope.

* Model Type: LoRA
* Base Model: [Tongyi-MAI/Z-Image-Turbo](https://modelscope.ai/models/Tongyi-MAI/Z-Image-Turbo)
* Training Code: [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio)
* Data amount：20
* Total training steps：4000
* License: Apache-2.0

## Inference Code

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

```bash
pip install diffsynth
```

Inference:

```python
from diffsynth.pipelines.z_image import ZImagePipeline, ModelConfig
import torch

pipe = ZImagePipeline.from_pretrained(
    torch_dtype=torch.bfloat16,
    device="cuda",
    model_configs=[
        ModelConfig(model_id="Tongyi-MAI/Z-Image-Turbo", origin_file_pattern="transformer/*.safetensors"),
        ModelConfig(model_id="Tongyi-MAI/Z-Image-Turbo", origin_file_pattern="text_encoder/*.safetensors"),
        ModelConfig(model_id="Tongyi-MAI/Z-Image-Turbo", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
    ],
    tokenizer_config=ModelConfig(model_id="Tongyi-MAI/Z-Image-Turbo", origin_file_pattern="tokenizer/"),
)
pipe.load_lora(pipe.dit, ModelConfig(model_id="jlhe2016/ZimageTurbo-leiNano", origin_file_pattern="ZimageTurbo-leiNano_c1-st4000.safetensors"))
prompt = "a cat"
image = pipe(prompt=prompt, num_inference_steps=8, cfg_scale=1)
image.save("image.jpg")
```


Files with SHA256: f90fbf6e702b415b9c85d654954d0226f17b67b22de67c9609659c8d89c8d42e