openai/improved-diffusion

Health v2 · maintenance only

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3844 stars · 547 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

The official codebase for OpenAI's Improved Denoising Diffusion Probabilistic Models paper, providing a Python package for training and sampling diffusion-based image generation models. It includes training scripts, dataset preparation utilities for ImageNet, LSUN, and CIFAR-10, and support for distributed GPU training.

Use cases

• train a diffusion model for image generation
• reproduce improved DDPM research results
• generate images from a trained denoising diffusion model
• train a class-conditional image generation model on my own dataset
• experiment with cosine noise schedules and learned sigmas in diffusion models
• run distributed training of generative image models on multiple GPUs

When to choose

• you want to train or fine-tune diffusion models from the improved DDPM paper
• you need a research-grade reference implementation of DDPM training and sampling
• you want to experiment with diffusion hyperparameters like noise schedules and learned sigmas

When to avoid

• you need a production-ready image generation API or pretrained model serving
• you want modern diffusion frameworks with schedulers like Diffusers
• you need text-to-image or latent diffusion capabilities

Facets

library · maturity maintenance

machine-learning deep-learning image-processing llm-training deep-learning machine-learning image-processing artificial-intelligence python diffusion-models ddpm generative-models image-generation research-code openai gpu linux

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