stable-diffusion-2-1

Maintainer: stabilityai

Total Score

3.7K

Last updated 5/28/2024

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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 stable-diffusion-2-1 model is a text-to-image generation model developed by Stability AI. It is a fine-tuned version of the stable-diffusion-2 model, with an additional 55k steps on the same dataset and then a further 155k steps with adjusted "unsafety" settings. Similar models include the stable-diffusion-2-1-base which fine-tunes the stable-diffusion-2-base model.

Model inputs and outputs

The stable-diffusion-2-1 model is a diffusion-based text-to-image generation model that takes text prompts as input and generates corresponding images as output. The text prompts are encoded using a fixed, pre-trained text encoder, and the generated images are 768x768 pixels in size.

Inputs

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

Outputs

  • Image: A 768x768 pixel image generated based on the input text prompt.

Capabilities

The stable-diffusion-2-1 model can generate a wide variety of images based on text prompts, from realistic scenes to fantastical creations. It demonstrates impressive capabilities in areas like generating detailed and complex images, rendering different styles and artistic mediums, and combining diverse visual elements. However, the model still has limitations in terms of generating fully photorealistic images, rendering legible text, and handling more complex compositional tasks.

What can I use it for?

The stable-diffusion-2-1 model is intended for research purposes only. Possible use cases include generating artworks and designs, creating educational or creative tools, and probing the limitations and biases of generative models. The model should not be used to intentionally create or disseminate images that could be harmful, offensive, or propagate stereotypes.

Things to try

One interesting aspect of the stable-diffusion-2-1 model is its ability to generate images with different styles and artistic mediums based on the text prompt. For example, you could try prompts that combine realistic elements with more fantastical or stylized components, or experiment with prompts that evoke specific artistic movements or genres. The model's performance may also vary depending on the language and cultural context of the prompt, so exploring prompts in different languages could yield interesting results.



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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