Kandinsky 2.1 inherits best practicies from Dall-E 2 and Latent diffusion, while introducing some new ideas.
As text and image encoder it uses CLIP model and diffusion image prior (mapping) between latent spaces of CLIP modalities. This approach increases the visual performance of the model and unveils new horizons in blending images and text-guided image manipulation.
For diffusion mapping of latent spaces we use transformer with num_layers=20, num_heads=32 and hidden_size=2048.
Kandinsky_2.1 huggingface.co is an AI model on huggingface.co that provides Kandinsky_2.1's model effect (), which can be used instantly with this ai-forever Kandinsky_2.1 model. huggingface.co supports a free trial of the Kandinsky_2.1 model, and also provides paid use of the Kandinsky_2.1. Support call Kandinsky_2.1 model through api, including Node.js, Python, http.
Kandinsky_2.1 huggingface.co is an online trial and call api platform, which integrates Kandinsky_2.1's modeling effects, including api services, and provides a free online trial of Kandinsky_2.1, you can try Kandinsky_2.1 online for free by clicking the link below.
ai-forever Kandinsky_2.1 online free url in huggingface.co:
Kandinsky_2.1 is an open source model from GitHub that offers a free installation service, and any user can find Kandinsky_2.1 on GitHub to install. At the same time, huggingface.co provides the effect of Kandinsky_2.1 install, users can directly use Kandinsky_2.1 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.