floyo logo
Powered by
ThinkDiffusion
floyo logo
Powered by
ThinkDiffusion

Create Character LoRA Dataset using Qwen Image Edit 2509

2.1k

Overview

  • Purpose: To generate a consistent, high-quality character dataset for training LoRA models.

  • Powered by: Qwen Image Edit 2509, known for its strong identity preservation and multi-image editing features.​​

  • Goal: Create multiple character images with varied poses, lighting, and expressions while maintaining consistent facial features and style.

Why Qwen Image Edit 2509 in creating lora dataset

  • Excels at preserving facial identity and style across multiple images, producing highly consistent datasets for character LoRA training.​

  • Lower tendency for artifacts or mismatched features, even with varied expressions, angles, or lighting.

  • offers superior identity consistency, easier batch dataset creation, and advanced multi-image control features, making it the go-to solution for LoRA character datasets—especially for creators who want fast, reliable, and contextually accurate results.

Read more

N
Generates in about 3 mins 56 secs

Nodes & Models

UNETLoader
qwen_image_edit_2509_fp8_e4m3fn.safetensors
Label (rgthree)
CLIPLoader
qwen_2.5_vl_7b_fp8_scaled.safetensors
VAELoader
qwen_image_vae.safetensors
LoadImage
LoraLoaderModelOnly
Qwen-Image-Lightning-4steps-V1.0.safetensors
lenovoqwen.safetensors
StringConcatenate
CLIPTextEncode
ImageScaleToTotalPixels
GetImageSize
TextEncodeQwenImageEditPlus
ModelSamplingAuraFlow
EmptyLatentImage
KSampler
VAEDecode
PreviewImage
Text Multiline
CR Prompt List
SaveImageKJ
SaveImageKJ

Overview

  • Purpose: To generate a consistent, high-quality character dataset for training LoRA models.

  • Powered by: Qwen Image Edit 2509, known for its strong identity preservation and multi-image editing features.​​

  • Goal: Create multiple character images with varied poses, lighting, and expressions while maintaining consistent facial features and style.

Why Qwen Image Edit 2509 in creating lora dataset

  • Excels at preserving facial identity and style across multiple images, producing highly consistent datasets for character LoRA training.​

  • Lower tendency for artifacts or mismatched features, even with varied expressions, angles, or lighting.

  • offers superior identity consistency, easier batch dataset creation, and advanced multi-image control features, making it the go-to solution for LoRA character datasets—especially for creators who want fast, reliable, and contextually accurate results.

Read more

N