A Neural Language Style Transfer framework to transfer natural language text smoothly between fine-grained language styles like formal/casual, active/passive, and many more. Created by Prithiviraj Damodaran. Open to pull requests and other forms of collaboration.

A Dual Reinforcement Learning Framework for Unsupervised Text Style Transfer (IJCAI 2019)

StyleLLM文风大模型：基于大语言模型的文本风格迁移项目。Text style transfer base on Large Language Model. #文字修饰 # 润色 #风格模仿

Code for "Controllable Unsupervised Text Attribute Transfer via Editing Entangled Latent Representation" (NeurIPS 2019)

Implementation of "Disentangled Representation Learning for Non-Parallel Text Style Transfer(ACL 2019)" in Pytorch

A list of resources about Text Style Transfer

Text style transfer benchmark

The source code of Text Style Transfer via Learning Style Instance Supported Latent Space (IJCAI 2020).

Implementation of CycleGAN for Text style transfer with PyTorch.

Thank you BART! Rewarding Pre-Trained Models Improves Formality Style Transfer (ACL 2021)

金庸和古龙之间的文本风格转换

Style transfer in text using cycle-consistent WGANs

Implementation of INLG 19 paper: Rethinking Text Attribute Transfer: A Lexical Analysis

Code for "Data-to-text Generation with Style Imitation." [Findings of EMNLP 2020]

About, prompt-based few-shot learning, Text Generation with Prompting

Repository for author masking

A neural text style transfer model

Multilingual Pre-training with Language and Task Adaptation for Multilingual Text Style Transfer (ACL 2022)

Generic resources are what you need: Style transfer tasks without task-specific parallel training data (EMNLP 2021)

A slick text style transfer framework.