🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.

Mapping a variable-length sentence to a fixed-length vector using BERT model

Natural Language Processing Tutorial for Deep Learning Researchers

大规模中文自然语言处理语料 Large Scale Chinese Corpus for NLP

Google AI 2018 BERT pytorch implementation

💥Fast State-of-the-Art Tokenizers optimized for Research and Production

An Implementation of ERNIE For Language Understanding (including Pre-training models and Fine-tuning tools)

Pre-Training with Whole Word Masking for Chinese BERT（中文BERT-wwm系列模型）

Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning And private Server services

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

A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

Toolkit for Machine Learning, Natural Language Processing, and Text Generation, in TensorFlow

Tool for visualizing attention in the Transformer model (BERT, GPT-2, Albert, XLNet, RoBERTa, CTRL, etc.)

Implementation of BERT that could load official pre-trained models for feature extraction and prediction

A curated list of pretrained sentence and word embedding models

bert nlp papers, applications and github resources, including the newst xlnet ， BERT、XLNet 相关论文和 github 项目

pycorrector is a toolkit for text error correction. It was developed to facilitate the designing, comparing, and sharing of deep text error correction models.

State of the Art Natural Language Processing

Super easy library for BERT based NLP models

⭕ N2O: Distributed Application Server — https://ws.n2o.dev

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

RoBERTa中文预训练模型: RoBERTa for Chinese

Datasets, tools, and benchmarks for representation learning of code.

Documents, papers and codes related to Natural Language Processing, including Topic Model, Word Embedding, Named Entity Recognition, Text Classificatin, Text Generation, Text Similarity, Machine Translation)，etc. All codes are implemented intensorflow 2.0.

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

The jiant toolkit for general-purpose text understanding models

Aspect Based Sentiment Analysis, PyTorch Implementations. 基于方面的情感分析，使用PyTorch实现。

Use Google's BERT for named entity recognition （CoNLL-2003 as the dataset）.

🏡 Fast & easy transfer learning for NLP. Harvesting language models for the industry.