Boreal

Introduction

Boreal-FD is an experimental text-to-image model designed to generate more realistic and complex images using the Flux-Dev framework. It aims to overcome limitations in photographic aesthetics by enhancing skin texture, dynamic poses, and scene complexity.

Architecture

Boreal-FD utilizes LoRA (Low-Rank Adaptation) techniques on the Flux-Dev model, which is part of the stable-diffusion framework. It is trained with the Boring Reality image datasets to steer the model towards photorealism and diverse compositions.

Training

The model is in the early stages of development, undergoing continuous refinement. Training focuses on reducing shallow depth of field effects, improving skin texture, and increasing the complexity of scenes. It employs various training steps, with the current emphasis on balancing undertrained and overtrained LoRAs.

Guide: Running Locally

1. Clone the Repository: Obtain the model files from the Boreal repository.
2. Install Dependencies: Ensure you have the necessary libraries, such as PyTorch and Hugging Face's Transformers.
3. Download Weights: Access the Safetensors format weights from the Files & versions tab.
4. Run the Model: Use compatible tools like ComfyUI to generate images. Adjust LoRA strengths (0.5-2.0) and guidance settings (3.0-5.0) for optimal results.
5. Hardware Requirements: For better performance, consider using cloud-based GPUs from providers such as AWS, Google Cloud, or Azure.

License

The model is available under the terms specified in the repository's license file. Please review it to understand usage rights and restrictions.