# Welcome to Stable Diffusion

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**tip:** Stable Diffusion  is primarily used to generate detailed images conditioned on text descriptions, though it can also be applied to other tasks such as inpainting, outpainting, and generating image-to-image translations guided by a text prompt.
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## Abstract

Stable Diffusion is a latent diffusion model, a kind of deep generative neural network developed by the CompVis group at LMU Munich. The model has been released by a collaboration of Stability AI, CompVis LMU, and Runway with support from EleutherAI and LAION. In October 2022, Stability AI raised US$101 million in a round led by Lightspeed Venture Partners and Coatue Management.

Stable Diffusion's code and model weights have been released publicly, and it can run on most consumer hardware equipped with a modest GPU with at least 8 GB VRAM. This marked a departure from previous proprietary text-to-image models such as DALL-E and Midjourney which were accessible only via cloud services.

## Quick links

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[Technology](/overview/stable-diffusion-overview/technology.md)
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[License](/overview/stable-diffusion-overview/license.md)
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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://stablediffusion.gitbook.io/overview/welcome-to-stable-diffusion.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.