BERT最近太火，蹭个热点，整理一下相关的资源，包括Paper, 代码和文章解读。
1、Google官方:
1) BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
一切始于10月Google祭出的这篇Paper, 瞬间引爆整个AI圈包括自媒体圈: https://arxiv.org/abs/1810.04805
2) Github: https://github.com/google-research/bert
11月Google推出了代码和预训练模型，再次引起群体亢奋。
3) Google AI Blog: Open Sourcing BERT: State-of-the-Art Pre-training for Natural Language Processing
2、第三方解读：
1) 张俊林博士的解读， 知乎专栏：从Word Embedding到Bert模型—自然语言处理中的预训练技术发展史
我们在AINLP微信公众号上转载了这篇文章和张俊林博士分享的PPT，欢迎关注：
5) BERT Explained: State of the art language model for NLP
6) BERT介绍
9) 干货 | BERT fine-tune 终极实践教程: 奇点智能BERT实战教程，在AI Challenger 2018阅读理解任务中训练一个79+的模型。
10) 【BERT详解】《Dissecting BERT》by Miguel Romero Calvo
Dissecting BERT Part 1: The Encoder
Understanding BERT Part 2: BERT Specifics
Dissecting BERT Appendix: The Decoder
11）BERT+BiLSTM-CRF-NER用于做ner识别
12）AI赋能法律 | NLP最强之谷歌BERT模型在智能司法领域的实践浅谈
3、第三方代码：
1) pytorch-pretrained-BERT: https://github.com/huggingface/pytorch-pretrained-BERT
Google官方推荐的PyTorch BERB版本实现，可加载Google预训练的模型：PyTorch version of Google AI's BERT model with script to load Google's pre-trained models
2) BERT-pytorch: https://github.com/codertimo/BERT-pytorch
另一个Pytorch版本实现：Google AI 2018 BERT pytorch implementation
3) BERT-tensorflow: https://github.com/guotong1988/BERT-tensorflow
Tensorflow版本：BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
4) bert-chainer: https://github.com/soskek/bert-chainer
Chanier版本: Chainer implementation of "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding"
5) bert-as-service: https://github.com/hanxiao/bert-as-service
将不同长度的句子用BERT预训练模型编码，映射到一个固定长度的向量上：Mapping a variable-length sentence to a fixed-length vector using pretrained BERT model
这个很有意思，在这个基础上稍进一步是否可以做一个句子相似度计算服务？有没有同学一试？
6) bert_language_understanding: https://github.com/brightmart/bert_language_understanding
BERT实战：Pre-training of Deep Bidirectional Transformers for Language Understanding: pre-train TextCNN
7) sentiment_analysis_fine_grain: https://github.com/brightmart/sentiment_analysis_fine_grain
BERT实战，多标签文本分类，在 AI Challenger 2018 细粒度情感分析任务上的尝试：Multi-label Classification with BERT; Fine Grained Sentiment Analysis from AI challenger
8) BERT-NER: https://github.com/kyzhouhzau/BERT-NER
BERT实战，命名实体识别: Use google BERT to do CoNLL-2003 NER !
9) BERT-keras: https://github.com/Separius/BERT-keras
Keras版: Keras implementation of BERT with pre-trained weights
10) tbert: https://github.com/innodatalabs/tbert
PyTorch port of BERT ML model
11) BERT-Classification-Tutorial: https://github.com/Socialbird-AILab/BERT-Classification-Tutorial
12) BERT-BiLSMT-CRF-NER: https://github.com/macanv/BERT-BiLSMT-CRF-NER
Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning
13) bert-Chinese-classification-task
bert中文分类实践
14) bert-chinese-ner: https://github.com/ProHiryu/bert-chinese-ner
使用预训练语言模型BERT做中文NER
15）BERT-BiLSTM-CRF-NER
Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning
16) bert-sequence-tagging: https://github.com/zhpmatrix/bert-sequence-tagging
基于BERT的中文序列标注
持续更新，BERT更多相关资源欢迎补充，欢迎关注我们的微信公众号：AINLP
注：原创文章，转载请注明出处及保留链接“我爱自然语言处理”：https://www.52nlp.cn