Model card
SD Turbo is a distilled version of Stable Diffusion designed specifically for real-time image synthesis. Unlike standard diffusion models that require multiple sampling steps, SD Turbo utilizes Adversarial Diffusion Distillation (ADD) to generate high-quality images in just one to four steps. For developers, this means a drastic reduction in inference latency and compute costs, making it ideal for interactive applications, live prototyping, and edge deployment. It integrates seamlessly into existing Stable Diffusion pipelines, allowing you to swap the checkpoint for near-instantaneous text-to-image generation without needing a massive GPU cluster to maintain a responsive user experience.
Model files and versions
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We recommend using the ModelScope CLI or SDK. Install ModelScope first, then choose a full snapshot, single file, SDK or Git LFS workflow.
stabilityai/sd-turboInstall the CLI and SDK dependency before downloading.
pip install modelscopeDownload the complete weights, configuration and model card.
modelscope download --model stabilityai/sd-turboREADME.md is used as an example; replace it with another repository file when needed.
modelscope download --model stabilityai/sd-turbo README.md --local_dir ./dirUseful in Python projects and automation scripts.
from modelscope import snapshot_download
model_dir = snapshot_download('stabilityai/sd-turbo')Make sure Git LFS is installed correctly.
git lfs install
git clone https://www.modelscope.cn/stabilityai/sd-turbo.gitFetch the repository structure first, then pull large files when needed.
GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/stabilityai/sd-turbo.gitHow to use
- 01Step 1
Read the model card and source information.
- 02Step 2
Start with a small, non-sensitive evaluation.
- 03Step 3
Review quality, licensing and usage limits.
- 04Step 4
Adopt it only after validation.
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