ai-forever / kandinsky-2.2

multilingual text2image latent diffusion model

  • Public
  • 9.8M runs
  • GitHub
  • License

Input

Output

Run time and cost

This model runs on Nvidia A100 (40GB) GPU hardware. Predictions typically complete within 2 seconds.

Readme

Kandinsky 2.2

Kandinsky 2.2 brings substantial improvements upon its predecessor, Kandinsky 2.1, by introducing a new, more powerful image encoder - CLIP-ViT-G and the ControlNet support.

The switch to CLIP-ViT-G as the image encoder significantly increases the model’s capability to generate more aesthetic pictures and better understand text, thus enhancing the model’s overall performance.

The addition of the ControlNet mechanism allows the model to effectively control the process of generating images. This leads to more accurate and visually appealing outputs and opens new possibilities for text-guided image manipulation.