flux dev panorama lora 2

Introduction

The FLUX.1-[DEV] PANORAMA LORA (V2) is a LoRA model built to generate panoramas from text prompts using the Flux development framework. It is particularly suited for producing HDRI (High Dynamic Range Imaging) panoramic views.

Architecture

The model leverages the diffusers library and is based on the black-forest-labs/FLUX.1-dev model. It has been trained on images with a 2:1 aspect ratio (2048x1024), although it can handle different resolutions effectively.

Training

The model is optimized for generating panoramic images with a 2:1 ratio. It generalizes well across various resolutions, such as 1536 × 640 (~21:9), which is used for fast processing on the Hugging Face Inference API.

Guide: Running Locally

To run the FLUX.1-[DEV] PANORAMA LORA model locally, follow these steps:

1. Environment Setup:

   • Install Python and necessary dependencies.
   • Ensure you have the diffusers library installed.

2. Clone the Model Repository:

   • Use git to clone the model repository from Hugging Face.

3. Download Model Weights:

   • Access the model weights through Hugging Face's interface or API.

4. Run Inference:

   • Load the model and use sample prompts to generate images.

5. Optimize for Performance:

   • Consider using cloud-based GPUs for better performance. Recommended options include AWS EC2 instances, Google Cloud GPUs, or Azure's N-series VMs.

License

The model is released under the flux-1-dev-non-commercial-license. It is intended for non-commercial, personal, or demonstration purposes only, as it uses data from Google Street View. For more details, refer to the license document.