sd-turbo

Maintainer: stabilityai

Total Score

322

Last updated 5/28/2024

PropertyValue
Model LinkView on HuggingFace
API SpecView on HuggingFace
Github LinkNo Github link provided
Paper LinkNo paper link provided

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Model overview

The sd-turbo model is a fast generative text-to-image model developed by Stability AI. It is a distilled version of the Stable Diffusion 2.1 model, trained for real-time image synthesis. The model uses a novel training method called Adversarial Diffusion Distillation (ADD) to leverage large-scale diffusion models as a teacher signal and combine it with an adversarial loss to ensure high image fidelity even with just 1-4 sampling steps.

The sd-turbo model can be compared to the SDXL-Turbo model, which is also a fast text-to-image model developed by Stability AI. SDXL-Turbo is based on the larger SDXL 1.0 model and uses the same Adversarial Diffusion Distillation training approach.

Model inputs and outputs

Inputs

  • Text prompt: A natural language description of the desired output image.

Outputs

  • Image: A 512x512 pixel image generated based on the input text prompt.

Capabilities

The sd-turbo model is capable of synthesizing photorealistic images from text prompts in a single network evaluation, making it a fast and efficient text-to-image generation model. The model can be used to create a wide variety of images, from realistic scenes to abstract and imaginative compositions.

What can I use it for?

The sd-turbo model is intended for both non-commercial and commercial usage. Possible use cases include:

  • Research on generative models: Studying the capabilities and limitations of real-time text-to-image generation models.
  • Real-time applications: Deploying the model in creative tools or applications that require fast image synthesis.
  • Artistic and design processes: Generating images for use in art, design, and other creative endeavors.
  • Educational tools: Incorporating the model into educational resources or interactive learning experiences.

For commercial use, users should refer to the Stability AI membership program.

Things to try

One key aspect of the sd-turbo model is its ability to generate high-quality images with just 1-4 sampling steps, which is significantly faster than traditional diffusion-based models. This makes the model well-suited for real-time applications and interactive use cases.

To get a sense of the model's capabilities, you could try generating images with a variety of prompts, from simple, everyday scenes to more complex, imaginative compositions. Pay attention to the model's ability to capture details, maintain coherence, and follow the intent of the prompt.

You could also experiment with the model's speed by comparing the quality and fidelity of images generated with different numbers of sampling steps. This could help you understand the tradeoffs between speed and image quality, and identify the optimal settings for your specific use case.



This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!

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