LoRA增强模板

使用LoRA增强图像生成效果的进阶模板。

模板概述

工作流结构

节点流程图(Mermaid)

graph TD
    A[CheckpointLoaderSimple] -->|MODEL| B[LoraLoader]
    A -->|CLIP| B

    B -->|MODEL| C[KSampler]
    B -->|CLIP| D[CLIPTextEncode]
    B -->|CLIP| E[CLIPTextEncode]
    B -->|VAE| F[VAEDecode]

    D -->|CONDITIONING| C
    E -->|CONDITIONING| C

    G[EmptyLatentImage] -->|LATENT| C

    C -->|LATENT| F
    F -->|IMAGE| H[SaveImage]

    style A fill:#e1f5ff
    style B fill:#fff4e1
    style C fill:#fff4e1
    style D fill:#ffe1f5
    style E fill:#ffe1f5
    style F fill:#e1ffe1
    style G fill:#e1ffe1
    style H fill:#ffe1e1

LoRA增强流程

graph LR
    A[主模型] --> B[加载LoRA]
    B --> C[增强模型]
    C --> D[采样生成]
    D --> E[高质量输出]

    style A fill:#e1ffe1
    style B fill:#fff4e1
    style C fill:#fff4e1
    style D fill:#fff4e1
    style E fill:#fff4e1

节点配置

1. CheckpointLoaderSimple

{
  "inputs": {
    "ckpt_name": "v1-5-pruned-emaonly.ckpt"
  },
  "class_type": "CheckpointLoaderSimple"
}

2. LoraLoader

{
  "inputs": {
    "lora_name": "detail_tweaker.safetensors",
    "strength_model": 0.8,
    "strength_clip": 0.8,
    "model": ["1", 0],
    "clip": ["1", 1]
  },
  "class_type": "LoraLoader"
}

3. CLIPTextEncode (正向)

{
  "inputs": {
    "text": "beautiful landscape, mountains, sunset, 4k, detailed",
    "clip": ["2", 1]
  },
  "class_type": "CLIPTextEncode"
}

4. CLIPTextEncode (负向)

{
  "inputs": {
    "text": "ugly, blurry, low quality",
    "clip": ["2", 1]
  },
  "class_type": "CLIPTextEncode"
}

5. EmptyLatentImage

{
  "inputs": {
    "width": 512,
    "height": 512,
    "batch_size": 1
  },
  "class_type": "EmptyLatentImage"
}

6. KSampler

{
  "inputs": {
    "seed": 123456789,
    "steps": 20,
    "cfg": 8.0,
    "sampler_name": "euler",
    "scheduler": "normal",
    "denoise": 1.0,
    "model": ["2", 0],
    "positive": ["3", 0],
    "negative": ["4", 0],
    "latent_image": ["5", 0]
  },
  "class_type": "KSampler"
}

7. VAEDecode

{
  "inputs": {
    "samples": ["6", 0],
    "vae": ["1", 2]
  },
  "class_type": "VAEDecode"
}

8. SaveImage

{
  "inputs": {
    "filename_prefix": "lora_",
    "images": ["7", 0]
  },
  "class_type": "SaveImage"
}

完整工作流JSON

{
  "1": {
    "inputs": {
      "ckpt_name": "v1-5-pruned-emaonly.ckpt"
    },
    "class_type": "CheckpointLoaderSimple"
  },
  "2": {
    "inputs": {
      "lora_name": "detail_tweaker.safetensors",
      "strength_model": 0.8,
      "strength_clip": 0.8,
      "model": ["1", 0],
      "clip": ["1", 1]
    },
    "class_type": "LoraLoader"
  },
  "3": {
    "inputs": {
      "text": "beautiful landscape, mountains, sunset, 4k, detailed",
      "clip": ["2", 1]
    },
    "class_type": "CLIPTextEncode"
  },
  "4": {
    "inputs": {
      "text": "ugly, blurry, low quality",
      "clip": ["2", 1]
    },
    "class_type": "CLIPTextEncode"
  },
  "5": {
    "inputs": {
      "width": 512,
      "height": 512,
      "batch_size": 1
    },
    "class_type": "EmptyLatentImage"
  },
  "6": {
    "inputs": {
      "seed": 123456789,
      "steps": 20,
      "cfg": 8.0,
      "sampler_name": "euler",
      "scheduler": "normal",
      "denoise": 1.0,
      "model": ["2", 0],
      "positive": ["3", 0],
      "negative": ["4", 0],
      "latent_image": ["5", 0]
    },
    "class_type": "KSampler"
  },
  "7": {
    "inputs": {
      "samples": ["6", 0],
      "vae": ["1", 2]
    },
    "class_type": "VAEDecode"
  },
  "8": {
    "inputs": {
      "filename_prefix": "lora_",
      "images": ["7", 0]
    },
    "class_type": "SaveImage"
  }
}

LoRA参数

Strength设置

graph TD
    A[LoRA Strength] --> B[0.3-0.5]
    A --> C[0.5-0.8]
    A --> D[0.8-1.2]

    B --> B1[轻微影响]
    C --> C1[标准强度]
    D --> D1[强烈影响]

    style A fill:#e1f5ff
    style B fill:#fff4e1
    style C fill:#ffe1f5
    style D fill:#e1ffe1

推荐配置

使用步骤

LoRA增强流程

graph LR
    A[加载主模型] --> B[加载LoRA]
    B --> C[设置提示词]
    C --> D[采样生成]
    D --> E[保存结果]

    style A fill:#e1ffe1
    style B fill:#fff4e1
    style C fill:#fff4e1
    style D fill:#fff4e1
    style E fill:#fff4e1

示例结果

示例1: 细节增强

示例2: 风格化

常见问题

Q1: LoRA strength设置多少?

A: 从0.8开始,根据效果调整,通常0.5-1.0。

Q2: 可以使用多个LoRA吗?

A: 可以,串联多个LoraLoader节点。

Q3: LoRA效果不明显?

A: 增加strength值,检查LoRA是否正确加载。

Q4: LoRA影响速度吗?

A: 轻微影响,但通常可以忽略。

Q5: 如何选择LoRA?

A: 根据需求选择,细节增强用detail类,风格化用风格类。

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