# dome272/Diffusion-Models-pytorch

Pytorch implementation of Diffusion Models (https://arxiv.org/pdf/2006.11239.pdf)

Repository: https://github.com/dome272/Diffusion-Models-pytorch
Canonical: https://ross.abutalabs.com/products/diffusion-models-pytorch
Language: Python
License: Apache-2.0
License Family: permissive
Last push: 2023-09-07T09:07:44+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1548, "days_push": 1091, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1458, forks 307 (observed 2026-08-28T04:04:47.135483+00:00)

## What it is
A minimal PyTorch implementation of DDPM diffusion models in under 100 lines of code, with conditional and unconditional variants including Classifier-Free Guidance and EMA. It is primarily an educational resource accompanied by explanation videos.

## Use cases
- learn how diffusion models work
- implement ddpm from scratch in pytorch
- train a diffusion model on my own images
- generate images with a diffusion model
- understand classifier-free guidance
- follow along with a diffusion models tutorial

## When to choose
- you want a short, readable implementation that follows the DDPM paper's Algorithm 1
- you are learning diffusion model theory and want code to match
- you need a starting point to train a small image diffusion model

## When to avoid
- you need production-grade training with efficient logging and performance
- you want state-of-the-art diffusion features like latent diffusion or advanced schedulers
- you need a maintained library with stable APIs and releases

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, deep-learning, image-processing
- domain: deep-learning, machine-learning, artificial-intelligence, tutorials
- platform: python
- tags: diffusion-models, ddpm, pytorch, image-generation, educational, classifier-free-guidance, gpu

## Member repositories
- dome272/Diffusion-Models-pytorch (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:47.135483+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:35:29.541625+00:00, confidence not recorded.
  - readme: https://github.com/dome272/Diffusion-Models-pytorch (fetched 2026-08-28T04:04:47.135483+00:00, sha 32d430673581)
- Data as of 2026-08-30T08:39:29.467469+00:00.