## 🧔 Mature Bald Coach —— Bear Middle-aged## 🧔 成熟光头教练 —— 熊中年Design Concept: This LoRA focuses on mature bald hairy bear coaches with thick dad bod, dense body hair and powerful yet approachable presence. Trained on Zimage turbo, it excels at realistic skin texture, and masculine middle-aged Asian/European bear charm.Key Features: Bald head, thick mustache, heavy chest, broad muscular shoulders, soft prominent belly, strong arms and thighs, mature masculine face (45-55), confident pose.Strengths: Excellent realistic body hair and skin rendering, stable bald head and hand proportions, strong dad bod performance, natural expressions and lighting adaptability.### 🔑 Trigger Words*<code>zhuang2xiong, bald man</code>**- Base Model: Zimage turbo (ZIT)- Strengthens mature bear middle-aged male features### 📋 Recommended Prompts1. Classic Style (Reference Image):zhuang2xiong bald man stands shirtless, wearing black leather shorts, with a broad, muscular build and a prominent mustache. His skin glistens slightly, suggesting sweat or oil, and his arms hang loosely at his sides. The background is a plain, neutral-colored room with angular ceiling lines. He looks directly at the camera with a serious expression.2. Gym Coach Scene:zhuang2xiong bald man, mature bear coach in his early 50s, shirtless with thick chest hair and soft prominent belly, broad muscular shoulders and veiny arms, bald head with thick mustache, standing confidently in gym, sweat on skin, powerful yet approachable expression, detailed realistic skin texture and body hair, warm gym lighting, highly detailed, photorealisticRecommended Settings:- Sampler: Euler- Steps: 20-30- CFG Scale: 4-5- LoRA Weight: 0.8-1.0- Resolution: 1024x1024Tips: Add <code>dense body hair, thick chest hair, prominent dad bod</code> for stronger bear features. Use natural language prompts for best results on Zimage turbo.Welcome to use and give feedback. If helpful, feel free to support me (BUZZ). Thank you!设计理念：专注成熟光头教练形象，强化厚实熊系身材、稳重有力的中年男性魅力。基于 Zimage turbo 训练，皮肤纹理、体毛细节与真实生活感表现优秀。核心特征：光头、浓密八字胡、、宽肩壮臂、软腹、强壮大腿、成熟男性面容（45-55岁）、自信站姿主要优势：体毛与皮肤写实度高、光头造型稳定、手部比例自然、熊系身材还原优秀、表情自然，适合健身教练、皮革、日常等多种中年熊场景。### 🔑 触发词 *<code>zhuang2xiong, bald man</code>**- 兼容底模：**Zimage turbo (ZIT)** - 强化熊中年男性特征### 📋 推荐 Prompt 示例1. 经典参考图风格： zhuang2xiong bald man stands shirtless, wearing black leather shorts, with a broad, muscular build and a prominent mustache. His skin glistens slightly, suggesting sweat or oil, and his arms hang loosely at his sides. The background is a plain, neutral-colored room with angular ceiling lines. He looks directly at the camera with a serious expression.2. 健身房教练场景： zhuang2xiong bald man, mature bear coach in his early 50s, shirtless with thick chest hair and soft prominent belly, broad muscular shoulders and veiny arms, bald head with thick mustache, standing confidently in gym, sweat on skin, powerful yet approachable expression, detailed realistic skin texture and body hair, warm gym lighting, highly detailed, photorealistic推荐生成设置：- Sampler: Euler- Steps: 20-30- CFG Scale: 4-5- LoRA 权重: 0.8-1.0- 分辨率: 1024x1024小贴士：加强体毛可添加 <code>dense body hair, thick chest hair, prominent dad bod</code>。

bald daddy  V2

zit_ba1da2dy_v1_c1-st6000.safetensors

v1.0


# 

## 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：19
* Total training steps：6000
* 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/zit_ba1da2dy_v1", origin_file_pattern="zit_ba1da2dy_v1_c1-st6000.safetensors"))
prompt = "a cat"
image = pipe(prompt=prompt, num_inference_steps=8, cfg_scale=1)
image.save("image.jpg")
```


Files with SHA256: 46a91e6dd59a625f7f3c82a40455df800e4d2cc7a38d8445a11259d08685d69e