bfelbo/DeepMoji
State-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc.
A Chinese news headline classification benchmark: 200K labeled samples across 10 categories. Covers 4 approaches — TF-IDF+RandomForest, FastText, BERT fine-tuning+int8 quantization, and knowledge distillation (BERT→TextCNN) — spanning classical ML to model compression, with Flask RESTful API.
$ git clone https://github.com/Happy-Chen-CH/text_classification.gitState-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc.
多标签文本分类,多标签分类,文本分类, multi-label, classifier, text classification, BERT, seq2seq,attention, multi-label-classification
Happy Transformer makes it easy to fine-tune and perform inference with NLP Transformer models.
情感分析、文本分类、词典、bayes、sentiment analysis、TextCNN、classification、tensorflow、BERT、CNN、text classification
Tensorflow based training and classification scripts for text, images, etc
Macadam是一个以Tensorflow(Keras)和bert4keras为基础,专注于文本分类、序列标注和关系抽取的自然语言处理工具包。支持RANDOM、WORD2VEC、FASTTEXT、BERT、ALBERT、ROBERTA、NEZHA、XLNET、ELECTRA、GPT-2等EMBEDDING嵌入; 支持FineTune、FastText、TextCNN、CharCNN、BiRNN、RCNN、DCNN、CRNN、DeepMoji、SelfAttention、HAN、Capsule等文本分类算法; 支持CRF、Bi-LSTM-CRF、CNN-LSTM、DGCNN、Bi-LSTM-LAN、Lattice-LSTM-Batch、MRC等序列标注算法。
Data from GitHub · snapshot Sep 24, 2026