chenyuntc/PyTorchText

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1057 stars · 360 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A PyTorch implementation of multiple text classification models (TextCNN, TextRNN/LSTM, RCNN, FastText, inception CNN) that won 1st place in the Zhihu Machine Learning Challenge 2017. It includes data preprocessing scripts, training pipelines, and model definitions for Chinese question topic classification.

Use cases

• classify Chinese questions into topics
• implement TextCNN TextRNN RCNN FastText models in PyTorch
• reproduce a winning text classification competition solution
• learn deep learning models for text classification
• train LSTM and CNN models on word and character embeddings

When to choose

• you need reference implementations of classic text classification models in PyTorch
• you are studying competition-winning NLP solutions
• you want to benchmark CNN/RNN/FastText approaches on Chinese text

When to avoid

• you need modern transformer-based models
• you require Python 3 support or active maintenance
• you need production-ready text classification services

Facets

library · maturity maintenance

machine-learning nlp deep-learning machine-learning deep-learning python pytorch text-classification textcnn lstm fasttext rcnn competition-solution kaggle-style natural-language-processing linux gpu

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