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