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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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