Naïve PAINE: Lightweight Text-to-Image Generation Improvement

Naïve PAINE (Prompt-Aware Inference Noise Evaluation) is a lightweight framework designed to transform random Gaussian noise into "golden noise." By adding a small, desirable perturbation derived from the text prompt, NPNet boosts the overall quality and semantic faithfulness of synthesized images.

Overview

This guide provides instructions on how to use the NPNet, a noise prompt network that transforms random Gaussian noise into golden noise. It is lightweight enough to seamlessly fit into existing DM pipelines.

Supported Models:

• Stable Diffusion XL
• DreamShaper-XL-v2-Turbo
• Hunyuan-DiT
• PixArt-Sigma

Requirements

• Python >= 3.10.0
• PyTorch (CUDA version)
• diffusers, transformers, accelerate, timm, einops, safetensors

Installation 🚀

git clone [https://github.com/LSU-ATHENA/Naive-PAINE.git](https://github.com/LSU-ATHENA/Naive-PAINE.git)
cd Naive-PAINE
pip install diffusers transformers accelerate torch torchvision timm einops safetensors