Flux 2 D Game Assets Lo R A

Introduction

The Flux-2D-Game-Assets-LoRA is a model designed for generating 2D game asset images using text-to-image pipelines. It leverages the capabilities of LoRA (Low-Rank Adaptation) and is hosted on Hugging Face, allowing users to create pixel art game assets from textual prompts.

Architecture

This model is based on the black-forest-labs/FLUX.1-dev base model and uses the diffusers library. It is tailored for text-to-image generation tasks, specifically optimized for creating pixel art game assets.

Training

The Flux-2D-Game-Assets-LoRA was trained using the FAL Fast LoRA Trainer, which is designed to optimize the training process of LoRA models efficiently. This approach ensures high-quality output with reduced computational demands.

Guide: Running Locally

To run the Flux-2D-Game-Assets-LoRA locally:

1. Install the required packages:

   pip install diffusers
   

2. Clone the repository:

   git clone https://huggingface.co/gokaygokay/Flux-2D-Game-Assets-LoRA
   cd Flux-2D-Game-Assets-LoRA
   

3. Load the model and generate images:

   from diffusers import StableDiffusionPipeline
   
   pipeline = StableDiffusionPipeline.from_pretrained("gokaygokay/Flux-2D-Game-Assets-LoRA")
   prompt = "GRPZA, green magic potion, white background, game asset, pixel art"
   image = pipeline(prompt).images[0]
   image.save("output.png")
   

4. Consider using cloud GPUs: To handle the computational load effectively, consider using cloud services like AWS, GCP, or Azure, which provide access to powerful GPUs.

License

The FLUX-2D-Game-Assets-LoRA model is released under the Apache 2.0 license, allowing for both personal and commercial use, modification, and distribution with proper attribution.