amirbar/rnn.wgan

Code for training and evaluation of the model from "Language Generation with Recurrent Generative Adversarial Networks without Pre-training"

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Emerging

This project helps machine learning researchers explore and develop new ways to generate realistic text without needing extensive pre-training. You provide it with a large dataset of text, and it produces new, similar-sounding text snippets. This tool is for researchers experimenting with generative adversarial networks (GANs) for language tasks.

252 stars. No commits in the last 6 months.

Use this if you are a researcher focused on advancing the field of text generation, specifically using GANs without pre-training.

Not ideal if you need a ready-to-use text generation tool for an application or if you are not comfortable with machine learning research workflows.

natural-language-generation generative-adversarial-networks text-synthesis machine-learning-research artificial-intelligence-experimentation
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 23 / 25

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Stars

252

Forks

76

Language

Python

License

Last pushed

Apr 11, 2018

Commits (30d)

0

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