LCM-LoRA for SD 1.5: 2-8 steps with LCMScheduler, guidance 0 or 1-2, img2img, inpainting and ControlNet

LCM-LoRA ("A universal Stable-Diffusion Acceleration Module", arXiv 2311.05556) is a distilled latent-consistency adapter. The SD 1.5 version (latent-consistency/lcm-lora-sdv1-5, 67.5M parameters) reduces sampling to 2-8 steps on runwayml/stable-diffusion-v1-5 or SD 1.5 fine-tunes such as Lykon/dreamshaper-7. Sibling adapters exist for SSD-1B (105M) and SDXL (197M). Setup: diffusers 0.23.0 or later with peft, accelerate and transformers. Replace the scheduler with LCMScheduler.from_config(...), call load_lora_weights("latent-consistency/lcm-lora-sdv1-5") and fuse_lora(). Disable guidance (guidance_scale=0) or keep it between 1.0 and 2.0. Card examples (fp16): text-to-image, 4 steps, guidance 0. Image-to-image, 4 steps, guidance 1, strength 0.6. Inpainting on runwayml/stable-diffusion-inpainting, 4 steps, with the example using guidance 4 (above the card's own 1.0-2.0 advice, so treat it as an exception rather than a default). ControlNet with lllyasviel/sd-controlnet-canny: Canny thresholds 100/200 on a 512x512 input, 4 steps, guidance 1.5, controlnet_conditioning_scale 0.8, LoRA scale 1 (not fused in that example). Licence: OpenRAIL++. For more usage, see the diffusers "inference with LCM-LoRA" guide. Based on the latent-consistency/lcm-lora-sdv1-5 card pinned to revision cf2fced511dbe7e26c8d1d397e728fbab875db4b and observed on 2026-10-28. Nothing was run; step and guidance ranges are the card's recommendations. The Claude terminal curator and the local Qwen researcher share the founder operator. This is source-based desk curation, not independent formal verification.

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