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Version 2.0 of Stable Diffusion brings numerous advancements. The most important new feature is the improved text-to-image model OpenCLIP.

In August 2022, AI startup Stability AI, together with RunwayML, LMU Munich, EleutherAI and LAION, released Stable Diffusion, an open-source image AI that was immediately well received by the community.

Stable Diffusion can be used online for a fee and with content filters, or downloaded for free and used locally without content restrictions. Version 2.0 continues this open source approach. Leading the way is Stability AI.

Improved text encoder and new image modes

For version 2.0, the team used OpenCLIP (Contrastive Language-Image Pre-training), an improved version of the multimodal AI system that learns visual concepts from natural language self-supervised. OpenCLIP was released by LAION in three versions in mid-September and is now implemented in Stable Diffusion. Stability AI supported the training of OpenCLIP. CLIP models can compute representations of images and text as embeddings and compare their similarity. In this way, an AI system can generate an image that matches a text.

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Thanks to this new text encoder, Stable Diffusion 2.0 can generate significantly better images compared to version 1.0, according to Stability AI. The model can generate images with resolutions of 512×512 and 769×768 pixels, which are then upscaled to 2048×2048 pixels by an upscaler diffusion model that is also new.

The new upscaler in action: The image on the left has 128×128 pixels, the image on the right was upscaled to 512×512. | Image: Stable Diffusion

The new Open CLIP model was trained with an “aesthetic dataset” compiled by Stability AI based on the LAION-5B dataset. Sexual and pornographic content was filtered beforehand.

Also new is a depth-to-image model that analyzes the depth of an input image and then uses text input to transform it into new motifs with the contours of the original image.

Depth analysis allows Stable Diffusion 2.0 to precisely transform existing subjects into new subjects that resemble the original image. | Image: Stable Diffusion

Stable Diffusion version 2.0 also gets an inpainting model that can be used to replace individual image elements within an existing image, such as painting a cap or VR headset on the head.

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Open source as a model for success

Despite the numerous improvements, Stable Diffusion version 2.0 should still run locally on a single powerful graphics card with sufficient memory.

We’ve already seen that, when millions of people get their hands on these models, they collectively create some truly amazing things. This is the power of open source: tapping the vast potential of millions of talented people who might not have the resources to train a state-of-the-art model, but who have the ability to do something incredible with one.

Stability AI

More information and access to the new models are available on Github. They should also be available for the Stable Diffusion web interface Dreamstudio in the coming days. Developers can find more information in the Stability AI API documentation.

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Summary
  • Stability AI introduces version 2.0 of its open-source image AI Stable Diffusion.
  • It contains numerous improvements, including the new text-to-image encoder OpenCLIP, which should result in significantly better images.
  • As before, Stable Diffusion 2.0 can be downloaded for free and run locally as an open-source model. The new models will also be available in the paid web version Dreamstudio in the coming days.
Online journalist Matthias is the co-founder and publisher of THE DECODER. He believes that artificial intelligence will fundamentally change the relationship between humans and computers.
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