tanelp/tiny-diffusion resource

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1014 stars · 81 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A minimal PyTorch implementation of probabilistic diffusion models (DDPM) trained on 2D point datasets like the Datasaurus Dozen. It includes visualizations of the forward and reverse diffusion processes plus ablation experiments on hyperparameters such as learning rate, timesteps, and variance schedules.

Use cases

• learn how diffusion models work
• understand ddpm training internals
• experiment with diffusion model hyperparameters
• visualize forward and reverse diffusion processes
• minimal diffusion model code to read and modify
• study effect of timestep count and beta schedules

When to choose

• you want a small, readable codebase to learn diffusion models from
• you need a sandbox for running ablations on DDPM hyperparameters
• you prefer minimal implementations over large production frameworks

When to avoid

• you need production-ready image or video diffusion generation
• you want pretrained models or a full feature set like HuggingFace diffusers
• you need a maintained library with a license and long-term support

Facets

learning-resource · maturity maintenance

machine-learning deep-learning data-visualization deep-learning machine-learning tutorials data-visualization python diffusion-models ddpm pytorch educational generative-models minimal-implementation

Member repositories

For agents

markdown · JSON · MCP: product_card(name="tanelp/tiny-diffusion")