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---
base_model: black-forest-labs/FLUX.1-dev
widget:
- text: yearbook portrait of student, plain background, smiling, teeth, braces
output:
url: images/7-1.png
- text: yearbook portrait of student, plain background, smiling, teeth, braces
output:
url: images/7-2.png
- text: yearbook portrait of student, plain background, smiling, teeth, braces
output:
url: images/7-3.png
- text: yearbook portrait of student, plain background, smiling, teeth, braces
output:
url: images/7-4.png
instance_prompt: braces
---
# Better Braces LoRA
<Gallery />
## Model description
This LoRA model specializes in generating portraits with braces, adding a realistic and distinctive touch to character images. Trained to excel at producing yearbook-style portraits with various styles of dental braces, it creates diverse and authentic representations.
The model aims to:
- Create diverse representations of braces on teeth
- Maintain natural facial expressions, particularly smiles
This LoRA is particularly useful for:
- Character designers seeking to add distinctive dental features
- Artists looking to create more diverse and realistic portraits
- Projects requiring specific orthodontic characteristics in images

While primarily focused on braces, the model maintains overall image quality and facial structure integrity.
## Trigger words
To activate this LoRA's specific features, include `braces` in your prompts.
## Download model
The weights for this model are available in Safetensors format.
You can [download](https://huggingface.co/Rejekts/Better-Braces/resolve/main/better-braces.safetensors) them in the Files & versions tab.
## Usage Tips
- Experiment with different strength settings to control the intensity of the braces effect
- Combine with other LoRAs or models for more diverse results
- Use negative prompts to fine-tune unwanted features if necessary
Remember, results may vary based on the base model and other parameters used in your generation pipeline.
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