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metadata
license: mit
language:
  - en
arxiv: 2603.12506
tags:
  - text-to-image

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.

arXiv GitHub Dataset

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