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
https://ai.googleblog.com/2018/11/open-sourcing-bert-state-of-art-pre.html
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
https://zhuanlan.zhihu.com/p/49271699
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:
2) 知乎: 如何评价 BERT 模型?
https://www.zhihu.com/question/298203515
3) 【NLP】Google BERT详解
https://zhuanlan.zhihu.com/p/46652512
https://blog.csdn.net/qq_39521554/article/details/83062188
5) BERT Explained: State of the art language model for NLP
https://towardsdatascience.com/bert-explained-state-of-the-art-language-model-for-nlp-f8b21a9b6270
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 !
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
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