Flux-Fine-Detail-LoRA
| Property | Value |
|---|---|
| Base Model | black-forest-labs/FLUX.1-dev |
| License | CreativeML OpenRAIL-M |
| Network Dimensions | 64 |
| Training Images | 15 |
| Optimal Dimensions | 768x1024, 1024x1024 |
What is Flux-Fine-Detail-LoRA?
Flux-Fine-Detail-LoRA is a specialized fine-tuning of the FLUX.1-dev model, designed to enhance detail generation in images. It employs LoRA (Low-Rank Adaptation) technology with carefully tuned parameters to achieve superior detail rendering in generated images. The model requires the trigger phrase "Super Detail" and is particularly effective at creating highly detailed portraits and close-up shots.
Implementation Details
The model utilizes an AdamW optimizer with a constant learning rate scheduler and implements specific noise parameters (offset: 0.03, discount: 0.1) across 10 epochs. The network architecture features a dimension of 64 with an alpha of 32, trained through 2470 steps with 15 repeats.
- Specialized noise handling with multires noise iterations: 10
- Network Alpha: 32 for balanced adaptation
- Training conducted over 10 epochs with checkpoints every epoch
- Florence2-en labeling system for natural language processing
Core Capabilities
- High-fidelity facial detail generation
- Enhanced texture rendering in close-up shots
- Optimal performance at 768x1024 resolution
- Specialized in portrait photography-style outputs
Frequently Asked Questions
Q: What makes this model unique?
This model's strength lies in its specialized fine-tuning for detail enhancement, particularly in facial features and close-up shots, achieved through careful parameter optimization and focused training on high-quality images.
Q: What are the recommended use cases?
The model excels at generating detailed portraits, close-up facial shots, and images requiring fine detail rendering. It's particularly effective when used with the specific dimensions of 768x1024 or 1024x1024.
