Challenges and Data Annotation in Krea 2 Character LoRA Training
4BEraser · reddit · 2026-07-20
The author shared the challenges and observations encountered while training an anime character LoRA for Krea 2:
- Highly Prompt-Dependent: Krea 2 follows prompts so strictly that traditional trigger words or phrases lose their effectiveness. This easily leads to simultaneous overfitting and underfitting of features (e.g., rigidly memorizing a specific halo while failing to learn the overall art style).
- Low Tolerance for Annotation Errors: Incorrect annotations auto-generated by VLMs severely hinder the model from learning true features. If the annotations don't match reality, the model will outright refuse to learn that design, sometimes resulting in worse outputs than using no LoRA at all.
The author calls on the community to exchange dataset annotation strategies for Krea 2, discussing whether purely manual annotation correction is necessary and how to effectively use negative prompts.
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