Gen-Verse/Diffusion-Sharpening
Diffusion-Sharpening: Fine-tuning Diffusion Models with Denoising Trajectory Sharpening
This project helps AI developers fine-tune large image generation models to produce better quality images. You input a pre-trained diffusion model and a dataset (or no dataset for online learning), along with a reward model to guide the training. The output is a fine-tuned diffusion model that generates images more aligned with specific quality criteria or user preferences.
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Use this if you are an AI researcher or developer looking to improve the output quality of your diffusion models, especially in terms of text-image alignment, human preference, or compositional accuracy, without incurring additional inference costs.
Not ideal if you are a casual user looking for an out-of-the-box image generation tool without diving into model training and configuration.
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Python
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Last pushed
May 18, 2025
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