Instructions to use stabilityai/sd-turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stabilityai/sd-turbo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/sd-turbo", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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README.md
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The charts above evaluate user preference for SD-Turbo over other single- and multi-step models.
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SD-Turbo evaluated at a single step is preferred by human voters in terms of image quality and prompt following over LCM-XL
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**Note:** For increased quality, we recommend the bigger version [SDXL-Turbo](https://huggingface.co/stabilityai/sdxl-turbo/).
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For details on the user study, we refer to the [research paper](https://stability.ai/research/adversarial-diffusion-distillation).
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The charts above evaluate user preference for SD-Turbo over other single- and multi-step models.
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SD-Turbo evaluated at a single step is preferred by human voters in terms of image quality and prompt following over LCM-Lora XL and LCM-Lora 1.5.
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**Note:** For increased quality, we recommend the bigger version [SDXL-Turbo](https://huggingface.co/stabilityai/sdxl-turbo/).
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For details on the user study, we refer to the [research paper](https://stability.ai/research/adversarial-diffusion-distillation).
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