#486 · Primary category： Education & Research
Sentence-VAE
PyTorch Re-Implementation of "Generating Sentences from a Continuous Space" by Bowman et al 2015 https://arxiv.org/abs/1511.06349
Project last updated：06/10/26
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Why we included this project
This is a compact PyTorch re-implementation of the 2015 Bowman et al. sentence variational autoencoder, the paper that showed how to train text generators in a continuous latent space. The code is short enough to read end to end, and the README walks through the training setup with ELBO, NLL, and KL curves plus sampled and interpolated sentences, so you can see what the model actually produces. It is not a production library, but it is a solid base for reproducing the paper's results, experimenting with KL annealing, or building your own VAE-based text model. Anyone learning how latent-variable models behave on language will find it easier to follow than the original Theano code.
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