This is a dual-character LoRA trained specifically to test character separation and identity bleed in multi-subject generations.
The two subjects were deliberately chosen to be extreme visual opposites so that any identity crossover becomes immediately obvious:
Character A: Goth woman wearing black fishnet and dark, high-contrast clothing
Character B: Handsome man in a clean, tailored business suit with formal styling
If facial features, clothing styles, or overall identity begin to mix — you’ll see it instantly.
This makes the LoRA ideal as a diagnostic and validation tool, not just a character model.
🎯 Intended Use
Testing dual-character prompts
Detecting identity bleed
Validating Z-Image workflows
Benchmarking multi-subject LoRA behavior
Training-pipeline experimentation
🔞 SFW / NSFW Notes
This LoRA can be used in both SFW and NSFW scenarios, depending entirely on your prompts and base model.
However:
It was not specifically trained on NSFW content
Any NSFW output is a result of model + prompt, not training data
🛠️ Want to Create Your Own Dual-Character LoRA?
This model is an example output of my dual-character training workflow.
If you’d like to build your own (with your own characters, styles, or concepts), the full workflow is available on my Patreon:
👉 https://patreon.com/loboforgeai
The workflow covers:
Dataset structure
Captioning strategy
Identity isolation techniques
Training settings
Common failure cases (and how to avoid them)
Description
Prompt:
Ken is a handsome young man in a business suit.
Dakota is a pretty young goth girl with long black hair and fishnet.
Start with one or both of these and then say what they are doing.
Example:
Ken is a handsome young man in a business suit.
Dakota is a pretty young goth girl with long black hair and fishnet.
Ken is feeding Dakota strawberries.