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mnist-vae
ChandraU/mnist-vae
mnist-vae is a machine learning model from ChandraU. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
This repository contains a Variational Autoencoder (VAE) trained on the MNIST handwritten digit dataset.
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Updated Aug 24, 2026
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At a glance
- License
- mit
- Access
- Public
- Created
- Aug 24, 2026
- Updated
- Aug 24, 2026
- SHA
- 68088ed6
Datasets
Model card
From the Hugging Face model README
MNIST Variational Autoencoder
This repository contains a Variational Autoencoder (VAE) trained on the MNIST handwritten digit dataset.
Model
- Model: Variational Autoencoder (VAE)
- Dataset: MNIST
- Framework: PyTorch
- Latent Dimension: 20
Description
The VAE learns a latent representation of handwritten digits and can reconstruct input images and generate new digit images from the latent space.
Training
The model is trained using:
- Reconstruction Loss
- KL Divergence
The total VAE loss is the combination of reconstruction loss and KL divergence.
- License
- mit
- Created
- Aug 24, 2026
- Updated
- Aug 24, 2026