sd turbo

---
pipeline_tag: text-to-image
inference: false
---

SD-Turbo Model Card

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SD-Turbo is a fast generative text-to-image model that can synthesize photorealistic images from a text prompt in a single network evaluation.
We release SD-Turbo as a research artifact, and to study small, distilled text-to-image models. For increased quality and prompt understanding,
we recommend SDXL-Turbo.

Please note: For commercial use, please refer to https://stability.ai/license.

Model Details

Model Description

• Developed by: Stability AI

• Funded by: Stability AI

• Model type: Generative text-to-image model

• Finetuned from model: Stable Diffusion 2.1

Model Sources

For research purposes, we recommend our generative-models Github repository (https://github.com/Stability-AI/generative-models),
which implements the most popular diffusion frameworks (both training and inference).

• Repository: https://github.com/Stability-AI/generative-models

• Paper: https://stability.ai/research/adversarial-diffusion-distillation

• Demo [for the bigger SDXL-Turbo]: http://clipdrop.co/stable-diffusion-turbo

Evaluation

Note: For increased quality, we recommend the bigger version SDXL-Turbo.
For details on the user study, we refer to the research paper.

Uses

Direct Use

The model is intended for both non-commercial and commercial usage. Possible research areas and tasks include

• Research on generative models.

• Research on real-time applications of generative models.

• Research on the impact of real-time generative models.

• Safe deployment of models which have the potential to generate harmful content.

• Probing and understanding the limitations and biases of generative models.

• Generation of artworks and use in design and other artistic processes.

• Applications in educational or creative tools.

For commercial use, please refer to https://stability.ai/membership.

Excluded uses are described below.

Diffusers

pip install diffusers transformers accelerate --upgrade

• Text-to-image:

SD-Turbo does not make use of guidance_scale or negative_prompt, we disable it with guidance_scale=0.0.
Preferably, the model generates images of size 512x512 but higher image sizes work as well.
A single step is enough to generate high quality images.

from diffusers import AutoPipelineForText2Image
import torch
pipe = AutoPipelineForText2Image.from_pretrained("stabilityai/sd-turbo", torch_dtype=torch.float16, variant="fp16")
pipe.to("cuda")
prompt = "A cinematic shot of a baby racoon wearing an intricate italian priest robe."
image = pipe(prompt=prompt, num_inference_steps=1, guidance_scale=0.0).images[0]

• Image-to-image:

When using SD-Turbo for image-to-image generation, make sure that num_inference_steps * strength is larger or equal
to 1. The image-to-image pipeline will run for int(num_inference_steps * strength) steps, *e.g.* 0.5 * 2.0 = 1 step in our example
below.

from diffusers import AutoPipelineForImage2Image
from diffusers.utils import load_image
import torch
pipe = AutoPipelineForImage2Image.from_pretrained("stabilityai/sd-turbo", torch_dtype=torch.float16, variant="fp16")
pipe.to("cuda")
init_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png").resize((512, 512))
prompt = "cat wizard, gandalf, lord of the rings, detailed, fantasy, cute, adorable, Pixar, Disney, 8k"
image = pipe(prompt, image=init_image, num_inference_steps=2, strength=0.5, guidance_scale=0.0).images[0]

Out-of-Scope Use

The model was not trained to be factual or true representations of people or events,
and therefore using the model to generate such content is out-of-scope for the abilities of this model.
The model should not be used in any way that violates Stability AI's Acceptable Use Policy.

Limitations and Bias

Limitations

• The quality and prompt alignment is lower than that of SDXL-Turbo.

• The generated images are of a fixed resolution (512x512 pix), and the model does not achieve perfect photorealism.

• The model cannot render legible text.

• Faces and people in general may not be generated properly.

• The autoencoding part of the model is lossy.

Recommendations

The model is intended for both non-commercial and commercial usage.

How to Get Started with the Model

Check out https://github.com/Stability-AI/generative-models