flux Realism Lora

Introduction

The FLUX-RealismLora model is a text-to-image generation model leveraging the FLUX.1-dev framework by Black Forest Labs. It utilizes LoRA (Low-Rank Adaptation) with Stable Diffusion to enhance photorealistic image generation.

Architecture

The model is based on the FLUX.1-dev framework, integrating LoRA to fine-tune its capabilities for photorealistic image generation. It supports various tags, including LoRA, Stable Diffusion, and diffusers, indicating its versatile application in image-generation tasks.

Training

The training process employs a structured dataset comprising images and their corresponding JSON files containing captions. The XLabs AI team provides scripts for fine-tuning using LoRA and ControlNet. Detailed train scripts and configurations are available in their GitHub repository.

Guide: Running Locally

To run the FLUX-RealismLora model locally, follow these steps:

1. Clone the Repository: Access the GitHub repository to clone the necessary files.
2. Set Up Environment: Install required dependencies and ensure you have Python 3 available.
3. Download Checkpoints: Obtain the lora.safetensors checkpoint file.
4. Run Inference: Execute the inference script with a sample command:

   python3 demo_lora_inference.py \
       --checkpoint lora.safetensors \
       --prompt "handsome girl in a suit covered with bold tattoos and holding a pistol. Animatrix illustration style, fantasy style, natural photo cinematic"
   

Suggested Cloud GPUs

For optimal performance, consider using cloud-based GPUs such as AWS EC2 instances with NVIDIA GPUs, Google Cloud's GPU offerings, or Azure's GPU services.

License

The lora.safetensors checkpoint and associated materials are released under the FLUX.1-dev Non-Commercial License. For more details, refer to the license document.