alshedivat/diffusion-playground
A playground for experimenting with diffusion models 🌀
This is a specialized toolkit for machine learning researchers and engineers who are building or studying diffusion models. It provides modular components for training diffusion models and generating new data from them. You input datasets like images (e.g., MNIST, CIFAR10) or 3D point clouds, and it helps you generate new, similar data or analyze how these generative models work. It's designed for those actively engaged in deep learning model development.
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Use this if you are a machine learning researcher or practitioner specifically working on developing, training, or experimenting with diffusion-based generative models for various data types.
Not ideal if you are looking for an off-the-shelf application to generate images or data without deep technical understanding or customization of diffusion model internals.
Stars
26
Forks
7
Language
Python
License
MIT
Category
Last pushed
Feb 26, 2024
Commits (30d)
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