# 649453932/chinese-text-classification-pytorch

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5,734 stars · 1,264 forks · Python · MIT

## Links

- GitHub: https://github.com/649453932/Chinese-Text-Classification-Pytorch
- awesome-repositories: https://awesome-repositories.com/repository/649453932-chinese-text-classification-pytorch.md

## Description

This project is a PyTorch-based framework and implementation suite for the supervised classification of Chinese text. It serves as a deep learning text classifier designed to automate the process of labeling and organizing Chinese language documents into predefined categories.

The framework provides a collection of neural network architectures, including TextCNN, Transformer, and FastText. It allows for the selection and prototyping of different model topologies through a modular implementation, enabling the evaluation of various sequence models on specific datasets.

The system covers a full deep learning natural language processing workflow, utilizing embedding-based text vectorization and attention-weighted sequence modeling to extract semantic patterns from raw text.

## Tags

### Artificial Intelligence & ML

- [Chinese Text Classifiers](https://awesome-repositories.com/f/artificial-intelligence-ml/chinese-text-classifiers.md) — Provides deep learning tools specifically designed to classify and categorize Chinese language documents. ([source](https://github.com/649453932/chinese-text-classification-pytorch#readme))
- [Deep Learning Classifiers](https://awesome-repositories.com/f/artificial-intelligence-ml/deep-learning-classifiers.md) — Provides a deep learning classifier framework for automating the labeling of Chinese text datasets.
- [Deep Learning NLP Frameworks](https://awesome-repositories.com/f/artificial-intelligence-ml/deep-learning-nlp-frameworks.md) — Integrates various neural network architectures into a comprehensive deep learning NLP workflow for text analysis.
- [Dense Vector Embeddings](https://awesome-repositories.com/f/artificial-intelligence-ml/dense-vector-embeddings.md) — Transforms Chinese characters into dense vector embeddings to capture semantic relationships for the neural network.
- [PyTorch Tensor Operations](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/infrastructure/model-optimization-and-inference/hardware-and-acceleration/tensor-computing-libraries/pytorch-tensor-operations.md) — Uses PyTorch for tensor operations and automatic differentiation to execute models on CPU or GPU.
- [Modular Architectures](https://awesome-repositories.com/f/artificial-intelligence-ml/neural-network-architectures/modular-architectures.md) — Provides a modular architecture allowing interchangeable backends such as CNN, RNN, and Transformer.
- [Supervised Classification](https://awesome-repositories.com/f/artificial-intelligence-ml/supervised-classification.md) — Implements a supervised classification pipeline to predict category labels from labeled text data.
- [Input Sequence Attentions](https://awesome-repositories.com/f/artificial-intelligence-ml/attention-mechanisms/input-sequence-attentions.md) — Implements attention weights to emphasize important information within input sequences for text classification.
- [Model Architecture Selection](https://awesome-repositories.com/f/artificial-intelligence-ml/model-architecture-selection.md) — Enables selection between different neural network topologies through a single configuration parameter.

### Web Development

- [Model Prototyping](https://awesome-repositories.com/f/web-development/state-management-models/state-space-models/deep-learning-frameworks/model-prototyping.md) — Supports rapid prototyping of multiple text classification architectures to evaluate accuracy on specific datasets.