Flux Mandala Lo R A

gokaygokay

Introduction

Flux-Mandala-LoRA is a text-to-image model designed to generate mandala drawings. It is part of the Hugging Face ecosystem, utilizing the diffusers library for image generation. This model is particularly effective for creating intricate mandala designs.

Architecture

The model is built on the black-forest-labs/FLUX.1-dev base model and employs the LoRA (Low-Rank Adaptation) technique for efficient fine-tuning. It leverages the diffusers library to transform text prompts into visually appealing mandala images.

Training

Flux-Mandala-LoRA was trained using the FAL Fast LoRA Trainer, which optimizes the training process for models using LoRA. This approach allows for faster training while maintaining high-quality output, specifically tailored for mandala artwork.

Guide: Running Locally

To run Flux-Mandala-LoRA locally, follow these basic steps:

  1. Clone the Repository:

    git clone https://huggingface.co/gokaygokay/Flux-Mandala-LoRA
    
  2. Install Dependencies: Ensure you have Python installed, then install the required libraries:

    pip install diffusers
    
  3. Load the Model: Use the diffusers library to load the model and generate images:

    from diffusers import DiffusionPipeline
    pipeline = DiffusionPipeline.from_pretrained("gokaygokay/Flux-Mandala-LoRA")
    
  4. Generate Images: Provide text prompts to generate mandala drawings:

    prompt = "Your text prompt here"
    image = pipeline(prompt)
    image.save("mandala.png")
    

Suggested Cloud GPUs: Utilizing cloud services like AWS, Google Cloud, or Azure with GPU instances can significantly enhance performance and reduce inference time.

License

Flux-Mandala-LoRA is released under the Apache 2.0 License, allowing for both commercial and non-commercial use, as long as the license terms are respected.

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