Flux-Realism-FineDetailed

Flux-Realism-FineDetailed

prithivMLmods

A fine-tuned LoRA model for FLUX.1-dev focused on photorealistic image generation with enhanced detail and texture quality. Trained on 27 curated images with constant LR scheduling and AdamW optimization.

PropertyValue
Base Modelblack-forest-labs/FLUX.1-dev
LicenseCreativeML OpenRAIL-M
Training Images27
Optimal Resolution1024x1024

What is Flux-Realism-FineDetailed?

Flux-Realism-FineDetailed is a specialized LoRA model designed to enhance the photorealistic capabilities of the FLUX.1-dev base model. It employs advanced training parameters including a constant learning rate scheduler and AdamW optimizer to achieve superior detail and texture quality in generated images.

Implementation Details

The model utilizes a network dimension of 64 and network alpha of 32, trained over 15 epochs with 3400 steps. It implements sophisticated noise handling with a 0.03 noise offset and multires noise iterations of 10, ensuring stable and high-quality image generation.

  • Constant learning rate scheduler with AdamW optimization
  • Network architecture: 64 dimensions with 32 alpha
  • Training protocol: 15 epochs with 3400 steps
  • Florence2-en labeling system for natural language processing

Core Capabilities

  • High-fidelity photorealistic image generation
  • Enhanced detail preservation in facial features and textures
  • Optimal performance at 1024x1024 resolution
  • Specialized in portrait and character generation

Frequently Asked Questions

Q: What makes this model unique?

This model's unique strength lies in its specialized training for fine detail preservation using carefully curated parameters and a small but high-quality training dataset of 27 images.

Q: What are the recommended use cases?

The model excels at generating photorealistic portraits, character images, and detailed scenes, particularly when triggered with the "Fine Detailed" prompt prefix.

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