CogVideoX is a text-to-video generation model focused on creating more coherent videos aligned with a prompt. It achieves this using several methods.  
- a 3D variational autoencoder that compresses videos spatially and temporally, improving compression rate and video accuracy.  
- an expert transformer block to help align text and video, and a 3D full attention module for capturing and creating spatially and temporally accurate videos.  
The actual test of the video instruction dimension found that CogVideoX has good effects on consistent theme, dynamic information, consistent background, object information, smooth motion, color, scene, appearance style, and temporal style but cannot achieve good results with human action, spatial relationship, and multiple objects.  
Finetuning with Diffusers can help make up for these poor results.
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/training/cogvideox.md