luosiallen/latent-consistency-model

Health v2 · maintenance only

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4615 stars · 232 forks observed · 2026-08-28

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

Official implementation of Latent Consistency Models (LCM), a diffusion-based approach for synthesizing high-resolution images with few-step inference, plus LCM-LoRA acceleration modules for Stable Diffusion. It includes inference code, training/distillation scripts, and model checkpoints for SD 1.5, SSD-1B, and SDXL.

Use cases

• generate images from text prompts in a few inference steps
• accelerate stable diffusion image generation with LCM-LoRA
• run fast text-to-image and image-to-image generation
• train or distill a latent consistency model on custom data
• build real-time image generation demos

When to choose

• you need fast few-step Stable Diffusion inference or LoRA acceleration
• you want to reproduce or build on the LCM research papers
• you need official checkpoints and training scripts for consistency distillation

When to avoid

• you need a production-grade maintained image generation pipeline rather than research code
• you want a general-purpose diffusion library like diffusers
• you need non-image modalities or the latest model architectures

Facets

library · maturity maintenance

machine-learning deep-learning image-processing artificial-intelligence image-processing deep-learning python stable-diffusion text-to-image few-step-inference lcm lcm-lora diffusion-models research-code gpu

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