TextGAN-PyTorch: benchmark GAN text-generation models

Understand the project

Practical overview

Use it when a research project calls for exploring GAN-based text generation in PyTorch and a shared framework for model runs and benchmarking.

Compare implementations of general text-generation GANs.
Experiment with category-conditioned text generation.
Run training workflows that record losses and metrics, save model states and generated samples, and visualize logs.
Use the repository's instructor structure as a starting point for adding a model.

Before you choose

The repository is public and lists an MIT license.

The documented stack specifies Python 3.6 and PyTorch 1.1.0 or later, along with NumPy, NLTK, tqdm and KenLM.
CUDA 7.5 or later is specified for GPU use; KenLM installation has additional Boost and bjam prerequisites.
The README lists four datasets for real-data experiments and includes a command pattern for launching model scripts.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up the repository and start a model script using the documented command pattern.

Clone the repository and change into its directory.
Install the Python requirements with the command below.
Documented command
```
pip install -r requirements.txt
```
Change into run and invoke a model script with job and GPU identifiers, following the example the command below.
Documented command
```
python3 run_seqgan.py 0 0
```

The documented workflow starts the selected model script with the supplied job and GPU identifiers.

GPU use requires CUDA; the README gives separate KenLM build prerequisites, including Boost and bjam.
The command is a documented usage example, not a guarantee of successful execution in a particular environment.

Evidence and transparency

Source record details

Source availability: Active
Sources checked: 15 October 2026
Original website title: williamSYSU/TextGAN-PyTorch · Official homepage title · retained in its source language