Kandinsky 2.0
Kandinsky 2.0 — the first multilingual text2image model.
UNet size: 1.2B parameters
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!
How to use
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)
