VainF/Diff-Pruning
[NeurIPS 2023] Structural Pruning for Diffusion Models
This project helps machine learning engineers and researchers optimize diffusion models for faster image generation and lower computational costs. You input a pre-trained diffusion model and a desired pruning ratio, and it outputs a smaller, more efficient diffusion model that retains high-quality image generation capabilities. This is for professionals working with generative AI who need to deploy models more efficiently.
218 stars. No commits in the last 6 months.
Use this if you need to reduce the computational footprint and inference time of large diffusion models while maintaining their creative output quality.
Not ideal if you are a casual user looking for an out-of-the-box image generation tool without needing to optimize model performance.
Stars
218
Forks
16
Language
Python
License
Apache-2.0
Category
Last pushed
Jul 08, 2024
Commits (30d)
0
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