ermongroup/ddim

Health v2 · maintenance only

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1845 stars · 231 forks observed · 2026-08-28

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

Official PyTorch implementation of Denoising Diffusion Implicit Models (DDIM), a faster sampling method for diffusion probabilistic models. It also integrates with the Hugging Face Diffusers library via the DDIMPipeline and DDIMScheduler.

Use cases

• generate images with diffusion models faster
• sample from DDPM models with fewer steps
• train a denoising diffusion model on CIFAR or other datasets
• use DDIM scheduler with Stable Diffusion
• reproduce DDIM paper FID experiments
• accelerate diffusion model inference

When to choose

• you want faster sampling from diffusion models with fewer steps
• you need the reference implementation of the DDIM paper
• you want a DDIM scheduler for Hugging Face Diffusers pipelines

When to avoid

• you need a maintained general-purpose diffusion library - use Hugging Face Diffusers instead
• you want production image generation without working with research code
• you need non-PyTorch frameworks

Facets

library · maturity maintenance

machine-learning deep-learning image-processing llm-inference deep-learning machine-learning image-processing artificial-intelligence python diffusion-models ddim ddpm image-generation generative-models sampling research-code pytorch gpu linux

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