What does your model do? What's it for?
This LoRA is a character concept model trained on a specific female aesthetic. It is designed to generate a highly detailed, consistent female character across various art styles, outfits, and environments using standard text prompts or image reference tools.
What is your model good at? What should it be used for?
Facial Consistency: Excellent at capturing a distinct facial structure, sharp jawline, and unique eye/hair features.
Versatility: Trained with
AdamW8Bitand acosine_with_restartsscheduler over 25 epochs (1,300 total steps) with a conservative learning rate, making it highly flexible and adaptable to different scene prompts without instantly burning the image.Style Adaptation: Works beautifully at standard weights (0.75 - 1.0) to place the subject into cinematic, casual, or fantasy settings.
What is your resource bad at? How should it not be used?
Sub-character Overlap: Because the dataset inherently includes a few visual variations (representing a mix of three distinct girl concepts from the training batch), generating with basic prompts might occasionally pull features from the other faces.
How NOT to use it: Avoid using it at full
1.0weight without descriptive prompt guidance if you want to isolate just one specific face. Do not use highly abstract, single-word prompts, or it may default back to mixing the three trained variations. For absolute face lock, it should be paired with Civitai's Reference Image tool set between 0.5 and 0.7 strength.
Description
What does your model do? What's it for?
This LoRA is a character concept model trained on a specific female aesthetic. It is designed to generate a highly detailed, consistent female character across various art styles, outfits, and environments using standard text prompts or image reference tools.
What is your model good at? What should it be used for?
Facial Consistency: Excellent at capturing a distinct facial structure, sharp jawline, and unique eye/hair features.
Versatility: Trained with
AdamW8Bitand acosine_with_restartsscheduler over 25 epochs (1,300 total steps) with a conservative learning rate, making it highly flexible and adaptable to different scene prompts without instantly burning the image.Style Adaptation: Works beautifully at standard weights (0.75 - 1.0) to place the subject into cinematic, casual, or fantasy settings.
What is your resource bad at? How should it not be used?
Sub-character Overlap: Because the dataset inherently includes a few visual variations (representing a mix of three distinct girl concepts from the training batch), generating with basic prompts might occasionally pull features from the other faces.
How NOT to use it: Avoid using it at full
1.0weight without descriptive prompt guidance if you want to isolate just one specific face. Do not use highly abstract, single-word prompts, or it may default back to mixing the three trained variations. For absolute face lock, it should be paired with Civitai's Reference Image tool set between 0.5 and 0.7 strength.