readme: ---
  license: apache-2.0
  tags:
  - Kandinsky
  - text-image
  - text2image
  - diffusion
  - latent diffusion
  - mCLIP-XLMR
  - mT5
  ---
  
  # Kandinsky 2.0
  
  
  Kandinsky 2.0 — the first multilingual text2image model.
  
  [Open In Colab](https://colab.research.google.com/drive/1uPg9KwGZ2hJBl9taGA_3kyKGw12Rh3ij?usp=sharing)
  
  [GitHub repository](https://github.com/ai-forever/Kandinsky-2.0)
  
  [Habr post](https://habr.com/ru/company/sberbank/blog/701162/)
  
  [Demo](https://rudalle.ru/)
  
  **UNet size: 1.2B parameters**
  
  ![NatallE.png](https://s3.amazonaws.com/moonup/production/uploads/1669132577749-5f91b1208a61a359f44e1851.png)
  
  It is a latent diffusion model with two multi-lingual text encoders:
  * mCLIP-XLMR (560M parameters)
  * mT5-encoder-small (146M parameters)
  
  
  These encoders and multilingual training datasets unveil the real multilingual text2image generation experience!
  
  ![header.png](https://s3.amazonaws.com/moonup/production/uploads/1669132825912-5f91b1208a61a359f44e1851.png)
  
  # How to use
  
  ```python
  pip install "git+https://github.com/ai-forever/Kandinsky-2.0.git"
  
  from kandinsky2 import get_kandinsky2
  model = get_kandinsky2('cuda', task_type='text2img')
  images = model.generate_text2img('кошка в космосе', batch_size=4, h=512, w=512, num_steps=75, denoised_type='dynamic_threshold', dynamic_threshold_v=99.5, sampler='ddim_sampler', ddim_eta=0.01, guidance_scale=10)
  ```
  
  # Authors
  
  + Arseniy Shakhmatov: [Github](https://github.com/cene555), [Blog](https://t.me/gradientdip)
  + Anton Razzhigaev: [Github](https://github.com/razzant), [Blog](https://t.me/abstractDL)
  + Aleksandr Nikolich: [Github](https://github.com/AlexWortega), [Blog](https://t.me/lovedeathtransformers)
  + Vladimir Arkhipkin: [Github](https://github.com/oriBetelgeuse)
  + Igor Pavlov: [Github](https://github.com/boomb0om)
  + Andrey Kuznetsov: [Github](https://github.com/kuznetsoffandrey)
  + Denis Dimitrov: [Github](https://github.com/denndimitrov)
  
  
  
  