LifangHe / TransformerCVAE

Transformer-based Conditional Variational Autoencoder for Controllable Story Generation

TransformerCVAE

This repository contains source code for paper Transformer-based Conditional Variational Autoencoder for Controllable Story Generation:

@article{fang2021transformer,
  title={Transformer-based Conditional Variational Autoencoder for Controllable Story Generation},
  author={Fang, Le and Zeng, Tao and Liu, Chaochun and Bo, Liefeng and Dong, Wen and Chen, Changyou},
  journal={arXiv preprint arXiv:2101.00828},
  year={2021}
}

0. get source data (Arxiv, Yelp, WritingPrompts, WikiPlots).
1. data pre-processing (data/).
2. training (choose from several different implementations on parallelism and precision: train.py, train_dist.py, train_dist_half.py).
3. generation, evaluation and analysis (generate.py/generate_prefix.py, eval_ppl.py/eval_ppl_prefix.py, tsne_plot.py).

Contact: [e-mail]

Update on 2022: If you encounter package version issue, sorry for that I don't have a requirements.txt with exact versions. I used this package: https://github.com/nvidia/apex and an old pytorch version compatible with it at that time, say pytorch=0.4 (not 100% sure).