<h3></h3><h1 id="real-strong-bald-daddy-or">Real strong bald daddy | 秃头壮爸写真</h1><h3 id="critical-warning-or">🔴 CRITICAL WARNING | 重要提醒</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-east-asian-strong-bald-daddy."><strong>[English]</strong> This model is a LoRA specialized in generating photorealistic East Asian strong bald daddy.</h3><ul><li><p>(Trigger: <code>wei nano</code>)</p></li></ul><h3 id="lora"><strong>[中文]</strong> 这是一个专用的 LoRA，专注于生成逼真的东方秃头壮爸。</h3><ul><li><p>触发词 ：<code>wei nano</code></p></li></ul><p></p>

Strong daddy——AS1DA3

zimageturbo_wei_nano_20.safetensors

zimageturbo-as1da3_c1-st3000.safetensors

v2.0 (ZImageTurbo)

v1.0 (flux.2 klein 4B)

v1.0(flux.2  klein 9b)


# 

## 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-as1da3", origin_file_pattern="zimageturbo-as1da3_c1-st4000.safetensors"))
prompt = "a cat"
image = pipe(prompt=prompt, num_inference_steps=8, cfg_scale=1)
image.save("image.jpg")
```


Files with SHA256: 9c648003cc94320eecc4016fdd52625545a6286d4444cbd4b73f3411bc6b68c3