riiid/PPAP
Official pytorch implementation of "Towards Practical Plug-and-Play Diffusion Models" in CVPR2023
This project helps machine learning engineers and researchers improve how well their image classification models perform, especially when using diffusion models. It takes an existing image dataset and a pre-trained diffusion model as input. It then outputs a more accurate and robust image classifier, enhancing performance compared to standard fine-tuning or single-expert approaches.
No commits in the last 6 months.
Use this if you are developing or training image classification models and want to leverage advanced techniques to achieve higher accuracy and more stable performance, particularly with diffusion-generated data.
Not ideal if you are looking for an out-of-the-box solution for image generation or if you don't have access to substantial computational resources for model training.
Stars
22
Forks
6
Language
Jupyter Notebook
License
Apache-2.0
Category
Last pushed
Jul 22, 2023
Commits (30d)
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