cgao96/nanoDiffusion
The simplest diffusion model in PyTorch, with Apple M chip acceleration support.
This project helps machine learning practitioners quickly experiment with and generate new images using diffusion models. It takes a dataset of images, like handwritten digits, and generates new, unique images that resemble the originals. Researchers and students learning about generative AI would find this useful for hands-on experience.
No commits in the last 6 months.
Use this if you want to understand or demonstrate how diffusion models work to generate images, especially on Apple M chip-powered Macs.
Not ideal if you need a production-ready, highly optimized, or feature-rich diffusion model for complex or large-scale image generation tasks.
Stars
41
Forks
1
Language
Python
License
—
Category
Last pushed
Jun 28, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/cgao96/nanoDiffusion"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
quantgirluk/aleatory
📦 Python library for Stochastic Processes Simulation and Visualisation
blei-lab/treeffuser
Treeffuser is an easy-to-use package for probabilistic prediction and probabilistic regression...
TuftsBCB/RegDiffusion
Diffusion model for gene regulatory network inference.
yuanchenyang/smalldiffusion
Simple and readable code for training and sampling from diffusion models
chairc/Integrated-Design-Diffusion-Model
IDDM (Industrial, landscape, animate, latent diffusion), support LDM, DDPM, DDIM, PLMS, webui...