# AutoencoderKLLTX2Audio

The 3D variational autoencoder (VAE) model with KL loss used in [LTX-2](https://huggingface.co/Lightricks/LTX-2) was introduced by Lightricks. This is for encoding and decoding audio latent representations.

The model can be loaded with the following code snippet.

```python
from diffusers import AutoencoderKLLTX2Audio

vae = AutoencoderKLLTX2Audio.from_pretrained("Lightricks/LTX-2", subfolder="vae", torch_dtype=torch.float32).to("cuda")
```

## AutoencoderKLLTX2Audio[[diffusers.AutoencoderKLLTX2Audio]]

#### diffusers.AutoencoderKLLTX2Audio[[diffusers.AutoencoderKLLTX2Audio]]

[Source](https://github.com/huggingface/diffusers/blob/v0.38.0/src/diffusers/models/autoencoders/autoencoder_kl_ltx2_audio.py#L668)

LTX2 audio VAE for encoding and decoding audio latent representations.

wrapperdiffusers.AutoencoderKLLTX2Audio.encodehttps://github.com/huggingface/diffusers/blob/v0.38.0/src/diffusers/utils/accelerate_utils.py#L43[{"name": "*args", "val": ""}, {"name": "**kwargs", "val": ""}]
#### wrapper[[diffusers.AutoencoderKLLTX2Audio.decode]]

[Source](https://github.com/huggingface/diffusers/blob/v0.38.0/src/diffusers/utils/accelerate_utils.py#L43)