crowsonkb/k-diffusion

Health v2 · maintenance only

Adoption not part of the score

2600 stars · 401 forks observed · 2026-08-28

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

A PyTorch library implementing Karras et al. (2022) diffusion models with enhancements like improved sampling algorithms and transformer-based diffusion architectures. It includes an hourglass diffusion transformer model type for image generation and training utilities.

Use cases

• train diffusion models for image generation in pytorch
• implement Karras et al 2022 diffusion sampling
• generate images with a diffusion transformer
• experiment with improved diffusion samplers
• train a text-to-image or class-conditional diffusion model
• research diffusion model design space

When to choose

• you need a faithful, enhanced implementation of Karras 2022 diffusion models in PyTorch
• you want state-of-the-art diffusion samplers like DPM++ or Heun
• you want to train or use hourglass diffusion transformer architectures
• you are doing research on diffusion model training and sampling

When to avoid

• you need a production image generation API with pretrained checkpoints out of the box
• you want a high-level framework like Hugging Face Diffusers with broad model support
• you work outside PyTorch or lack GPU resources
• you need simple plug-and-play inference without understanding diffusion internals

Facets

library · maturity active

machine-learning deep-learning image-processing machine-learning deep-learning image-processing python diffusion-models pytorch generative-models karras-diffusion image-generation sampling-algorithms transformer research gpu

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markdown · JSON · MCP: product_card(name="crowsonkb/k-diffusion")