A fast and flexible keyboard launcher

中文语言理解测评基准 Chinese Language Understanding Evaluation Benchmark: datasets, baselines, pre-trained models, corpus and leaderboard

A LITE BERT FOR SELF-SUPERVISED LEARNING OF LANGUAGE REPRESENTATIONS, 海量中文预训练ALBERT模型

🧠💬 Articles I wrote about machine learning, archived from MachineCurve.com.

Open Source Pre-training Model Framework in PyTorch & Pre-trained Model Zoo

Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)

中文长文本分类、短句子分类、多标签分类、两句子相似度（Chinese Text Classification of Keras NLP, multi-label classify, or sentence classify, long or short），字词句向量嵌入层（embeddings）和网络层（graph）构建基类，FastText，TextCNN，CharCNN，TextRNN, RCNN, DCNN, DPCNN, VDCNN, CRNN, Bert, Xlnet, Albert, Attention, DeepMoji, HAN, 胶囊网络-CapsuleNet, Transformer-encode, Seq2seq, SWEM, LEAM, TextGCN

Language Understanding Evaluation benchmark for Chinese: datasets, baselines, pre-trained models,corpus and leaderboard

a fast and user-friendly runtime for transformer inference (Bert, Albert, GPT2, Decoders, etc) on CPU and GPU.

CLUENER2020 中文细粒度命名实体识别 Fine Grained Named Entity Recognition

Tencent Pre-training framework in PyTorch & Pre-trained Model Zoo

Large-scale Pre-training Corpus for Chinese 100G 中文预训练语料

This repo contains a PyTorch implementation of a pretrained BERT model for multi-label text classification.

🤖 A PyTorch library of curated Transformer models and their composable components

高质量中文预训练模型集合：最先进大模型、最快小模型、相似度专门模型

A Lite Bert For Self-Supervised Learning Language Representations

自然语言处理工具Macropodus，基于Albert+BiLSTM+CRF深度学习网络架构，中文分词，词性标注，命名实体识别，新词发现，关键词，文本摘要，文本相似度，科学计算器，中文数字阿拉伯数字(罗马数字)转换，中文繁简转换，拼音转换。tookit(tool) of NLP，CWS(chinese word segnment)，POS(Part-Of-Speech Tagging)，NER(name entity recognition)，Find(new words discovery)，Keyword(keyword extraction)，Summarize(text summarization)，Sim(text similarity)，Calculate(scientif…

PyTorch implementation for "Matching the Blanks: Distributional Similarity for Relation Learning" paper

使用预训练语言模型ALBERT做中文NER

Models to perform neural summarization (extractive and abstractive) using machine learning transformers and a tool to convert abstractive summarization datasets to the extractive task.