CNNs for Sentence Classification in PyTorch

Character-level Convolutional Neural Networks for text classification in PyTorch

A simple implementation of CNN based text classification in Pytorch

The aim of this repository is to show a baseline model for text classification through convolutional neural networks in the PyTorch framework. The architecture implemented in this model was inspired by the one proposed in the paper: Convolutional Neural Networks for Sentence Classification.

中文二分类，bert+TextCNN 两种实现方法

CNN for Text Classification in Pytorch

Convolutional Neural Network (CNN) for text classification implemented with PyTorch and TorchText

Text Classification Models - CNN, RCNN, RNN-ATTN [PyTorch]

sentiment-analysis,document-classification,svm,logistic-regression,rcnn-text-classification, cnn-text-classification, lstm-text-classification, naive-bayes-classifier, sklearn-classify, pytorch

A pytorch implementation of the paper "Character-level Convolutional Networks for Text Classification"

PyTorch implementation of Y. Kim's 2015 CNN for text classification

PyTorch implementation of CNN for text classification

This repo contains a PyTorch implementation of a char-level CNN model for text classification.

Character-level text classification models with pytorch

Three PyTorch ML Projects: 1. MNIST Digit Classification (CNN) 2. IMDB Sentiment Analysis (Text Embedding + Feedforward) 3. California Housing Price Prediction (Regression NN). All scripts support GPU, include training, saving models.

PyTorch-Text-CNN-Classification

文本分类

CNNs for Sentence Classification in PyTorch

text classification using CNN with pytorch

No description available

No description available

CNN and RNN for Text Classification in Pytorch

CNN for Sentence/Text classification implemented in PyTorch (following PyTorch Lightning manners)

Implementation of text classification in pytorch using CNN/GRU/LSTM.

Implementations of CNN-LSTM and Transformer models in PyTorch for multi-category text classification.

PyTorch implementation of Yoon Kim's non-static single channel CNN for text classification

CNN-Text-Classifiers is a collection of Convolutional Neural Network–based models for text classification, built using PyTorch. Includes datasets, training scripts, evaluation utilities, and experiments comparing different CNN architectures for NLP tasks.

Multimodal Sentiment & Emotion Analysis on MELD using PyTorch and AWS SageMaker. Combines text, audio, and video features with BERT, 3D CNNs, and spectrogram-based audio encoders for joint emotion and sentiment classification.

Handwritten Text Recognition (HTR) system built with PyTorch and OpenCV. Features a robust pipeline for character segmentation, line/word grouping, and alphanumeric classification (0-9, A-Z, a-z) using high-accuracy CNNs. Includes Gradio web interfaces for both real-time OCR and single-character classification

Multimodal Fake News Detection This project detects fake news using BERT for text analysis and CNN for image processing, combining both for accurate classification. Built with PyTorch, it supports FakeNewsNet, LIAR, and custom datasets. Future improvements include web deployment, explainable AI, and larger datasets for better accuracy. 🚀