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# AutoencoderKLCogVideoX

The 3D variational autoencoder (VAE) model with KL loss used in [CogVideoX](https://github.com/THUDM/CogVideo) was introduced in [CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer](https://github.com/THUDM/CogVideo/blob/main/resources/CogVideoX.pdf) by Tsinghua University & ZhipuAI.

The model can be loaded with the following code snippet.

```python
from diffusers import AutoencoderKLCogVideoX

vae = AutoencoderKLCogVideoX.from_pretrained("THUDM/CogVideoX-2b", subfolder="vae", torch_dtype=torch.float16).to("cuda")
```

## AutoencoderKLCogVideoX

[[autodoc]] AutoencoderKLCogVideoX
    - decode
    - encode
    - all

## AutoencoderKLOutput

[[autodoc]] models.autoencoders.autoencoder_kl.AutoencoderKLOutput

## DecoderOutput

[[autodoc]] models.autoencoders.vae.DecoderOutput