Flux Mandala Lo R A
gokaygokayIntroduction
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:
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Clone the Repository:
git clone https://huggingface.co/gokaygokay/Flux-Mandala-LoRA
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Install Dependencies: Ensure you have Python installed, then install the required libraries:
pip install diffusers
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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")
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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.