Model architecture:
It is a latent diffusion model with two multilingual text encoders:
mCLIP-XLMR 560M parameters
mT5-encoder-small 146M parameters
These encoders and multilingual training datasets unveil the real multilingual text-to-image generation experience!
Kandinsky 2.0 was trained on a large 1B multilingual set, including samples that we used to train Kandinsky.
In terms of diffusion architecture Kandinsky 2.0 implements UNet with 1.2B parameters.
Proposed workflow
Ability to write Prompt in more than 100 languages.
Is there an existing issue for this?
What would your feature do ?
Kandinsky 2.0 - the first multilingual text2image model. https://github.com/ai-forever/Kandinsky-2.0 https://huggingface.co/sberbank-ai/Kandinsky_2.0
Model architecture: It is a latent diffusion model with two multilingual text encoders:
mCLIP-XLMR 560M parameters mT5-encoder-small 146M parameters These encoders and multilingual training datasets unveil the real multilingual text-to-image generation experience!
Kandinsky 2.0 was trained on a large 1B multilingual set, including samples that we used to train Kandinsky.
In terms of diffusion architecture Kandinsky 2.0 implements UNet with 1.2B parameters.
Proposed workflow
Ability to write Prompt in more than 100 languages.
Additional information
No response