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@@ -18,7 +18,7 @@ To learn discrete latent representations, ideas from vector quantisation (VQ) ar
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  This model has been trained using code from this [example](https://keras.io/examples/generative/vq_vae/), and a result of this [paper.](https://arxiv.org/pdf/1711.00937.pdf)
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  ## Model
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- Below we have a graphic from the paper above, showing the VQ-VAE model architecture.
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  ![VQ-VAE Model](vq.png)
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  ## Intended uses & limitations
 
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  This model has been trained using code from this [example](https://keras.io/examples/generative/vq_vae/), and a result of this [paper.](https://arxiv.org/pdf/1711.00937.pdf)
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  ## Model
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+ Below we have a graphic from the paper above, showing the VQ-VAE model architecture and quantization process.
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  ![VQ-VAE Model](vq.png)
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  ## Intended uses & limitations