Al-Kharba/EDM2

Unofficial implementation of EDM2: Analyzing and Improving the Training Dynamics of Diffusion Models

21
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Experimental

This project helps machine learning researchers and practitioners generate high-quality synthetic images using pre-trained diffusion models. You input parameters controlling the image generation process, and it outputs batches of diverse images and can also calculate metrics like Fréchet Inception Distance (FID) to evaluate the quality of the generated images. It's designed for users who need to generate realistic visual data or benchmark generative models.

No commits in the last 6 months.

Use this if you are a machine learning researcher or developer working with diffusion models and need to generate images or evaluate model performance efficiently.

Not ideal if you are looking for an out-of-the-box, user-friendly application for casual image generation without needing to engage with command-line tools and machine learning concepts.

generative AI diffusion models image synthesis machine learning research model evaluation
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 0 / 25

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12

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Language

Python

License

Last pushed

Mar 17, 2024

Commits (30d)

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