stable-diffusion-3-medium
Maintainer: stabilityai
850
❗
| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
stable-diffusion-3-medium is a cutting-edge Multimodal Diffusion Transformer (MMDiT) text-to-image generative model developed by Stability AI. It features significant improvements in image quality, typography, complex prompt understanding, and resource-efficiency compared to earlier versions of Stable Diffusion. The model utilizes three fixed, pretrained text encoders - OpenCLIP-ViT/G, CLIP-ViT/L, and T5-xxl - to enable these enhanced capabilities.
Model inputs and outputs
stable-diffusion-3-medium is a text-to-image model, meaning it takes text prompts as input and generates corresponding images as output. The model can handle a wide range of text prompts, from simple descriptions to more complex, multi-faceted prompts.
Inputs
- Text prompts describing the desired image
Outputs
- Generated images that match the input text prompts
Capabilities
stable-diffusion-3-medium excels at generating high-quality, photorealistic images from text prompts. It demonstrates significant improvements in areas like image quality, typography, and the ability to understand and generate images for complex prompts. The model is also resource-efficient, making it a powerful tool for a variety of applications.
What can I use it for?
stable-diffusion-3-medium can be used for a wide range of creative and professional applications, such as generating images for art, design, advertising, and even film and video production. The model's capabilities make it well-suited for projects that require visually striking, high-quality images based on text descriptions.
Things to try
One interesting aspect of stable-diffusion-3-medium is its ability to generate images with a strong sense of typography and lettering. You can experiment with prompts that include specific font styles or text compositions to see how the model handles these more complex visual elements. Additionally, you can try combining stable-diffusion-3-medium with other Stable Diffusion models, such as stable-diffusion-img2img or stable-diffusion-inpainting, to explore even more creative possibilities.
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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