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library_name: diffusers
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## EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling
Arxiv: https://arxiv.org/abs/2502.09509 <br>

**EQ-VAE** regularizes the latent space of pretrained autoencoders by enforcing equivariance under scaling and rotation transformations. 

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#### Model Description 
This model is a regularized version of [SD-VAE](https://github.com/CompVis/latent-diffusion). We finetune it with EQ-VAE regularization  for 44 epochs on Imagenet with EMA weights.


## Model Usage


2. **Loading the Model**  
   You can load the model from the Hugging Face Hub:
   ```python
   from transformers import AutoencoderKL
   model = AutoencoderKL.from_pretrained("zelaki/eq-vae-ema")

#### Metrics
Reconstruction performance of eq-vae-ema on Imagenet Validation Set.

| **Metric** | **Score** |
|------------|-----------|
| **FID**    | 0.552     |
| **PSNR**   | 26.158    |
| **LPIPS**  | 0.133     |
| **SSIM**   | 0.725     |
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