Flux AI SameFace Fix Lora: How to Get Unique Faces Every Time

The SameFace Problem in Flux AI

Users often encounter the "sameface" issue where the AI generates people with nearly identical appearances. This problem mainly arises because the Flux AI models, particularly the Dev and Schnell variants, lose diversity during the distillation process from the Pro version.

The Solution: SameFace Fix Lora

What is SameFace Fix Lora?

The SameFace Fix Lora is a specialized model designed to counteract the generic faces generated by Flux AI. Unlike traditional negative prompts, applying this Lora with a negative weight tells Flux AI to avoid generating the same repetitive faces, resulting in unique and beautiful outputs.

How to Apply the SameFace Fix Lora

Steps to Apply

1. Download the Model: First, download the SameFace Fix Lora from Civitai.
2. Load the Model: Integrate the model into your Flux AI interface.
3. Set the Weight: Apply the Lora with a negative weight. You can do this manually in the prompt window. For example: <lora:samefacefix:-0.5>
4. Generate Images: Enter your desired prompt and let Flux AI generate the images. You should see diverse faces instead of the typical "sameface."

Theoretical Background

The Lora works as a kind of negative prompt but is more effective. By setting a negative weight, you instruct the AI to exclude the features it usually relies on, thus generating a broader variety of faces.

Resource Links

For more detailed guidance, check out the discussion on Reddit at the permalink and the model page.

Detailed Operation and Effects

Initial Challenges and Solutions

The process initially faced issues and almost led to giving up. The breakthrough happened when the Lora was trained with just two layers, resulting in striking and diverse faces.

Effects

When you apply the Lora with a negative weight, Flux AI generates a broader variety of unique faces, overcoming the limitation of generating similar-looking images most of the time.

Optimizing Your Results

Experimenting with Layers

Different learning rates, layers, and ranks can be tested for optimal results. This includes experimenting with early and late layers (such as 7 and 20) to balance facial features and skin texture.

Merging Variants

Merging different Lora variants may help solve artifacting at higher values. This is particularly useful when you need to maintain high image quality without the issue of repetitive facial features.

Optimal Settings

For best results, try avoiding terms like "beautiful" in your prompts and consider including diverse names and ethnicities.

Applicable Scenarios

Use the SameFace Fix Lora in situations where diversity in facial features is crucial. It is particularly useful for creative projects that require unique character designs or varied facial features.

Limitations and Drawbacks

Focus on Female Faces

This model primarily targets women's faces. While the current version may not be equally effective for men, a future version for diversifying men's faces is planned.

Artifacts at Higher Values

Some users have reported artifacting at higher values, especially with hair. Additional fine-tuning is recommended to find the optimal balance.

FAQs

1. How do I apply the SameFace Fix Lora?

Set the Lora with a negative weight in your prompt, such as <lora:samefacefix:-0.5>.

2. What layers were used for this Lora?

The Lora uses layers 7 and 20, inspired by recommendations for balancing facial features and skin texture.

3. Can the Lora be used in scenes with multiple people?

Yes, but keep in mind it performs best on female faces. Experimentation is encouraged in varied scenarios.

4. Are there other ways to enhance facial diversity?

Avoid using generic terms like "beautiful" and include diverse names and ethnicities in your prompts.

5. How do I set the Lora weight in Forge?

Add the Lora in the prompt window manually, such as <lora:samefacefix:-0.5>, which overrides the default slider settings.

6. Will there be a version for men?

Yes, there's a plan to develop a future version aimed at diversifying men's faces.

User Questions and Additional FAQs

7. How do I integrate the SameFace Fix Lora with other Loras?

You can combine Loras by adding them in the prompt window with appropriate weights for each. For example: <lora:samefacefix:-0.5> <lora:anotherlora:0.8>

8. Can this Lora eliminate exaggerated features like a "butt-chin"?

Yes, setting a higher negative weight (-0.7 to -1.0) can help remove exaggerated features like a butt-chin.

9. What if I get noisy outputs?

Try adjusting the Lora weights or combining it with an upscale pass with a low denoise value, such as 0.25, to improve image quality.

10. Does using this Lora affect overall image quality?

While it mainly alters facial features, some users have noticed changes in overall image quality. Adjust weights and experiment to find what works best.

11. Can I use this Lora for other specific facial features?

Yes, the concept can be extended to other features by training custom Loras focused on those elements and applying them with negative weights.

12. How can I merge multiple negative Loras into one model?

You can merge multiple Loras by isolating their unique features and then combining them into one model. Tools like merging functions in VRAM can be useful.

By following these steps and considerations, you can make the most out of the SameFace Fix Lora and achieve truly unique faces with Flux AI!