nlp 预训练模型总结

• Google原版bert: https://github.com/google-research/bert
• brightmart版roberta: https://github.com/brightmart/roberta_zh
• 哈工大版roberta: https://github.com/ymcui/Chinese-BERT-wwm
• Google原版albert[例子]: https://github.com/google-research/ALBERT
• brightmart版albert: https://github.com/brightmart/albert_zh
• 转换后的albert: https://github.com/bojone/albert_zh
• 华为的NEZHA: https://github.com/huawei-noah/Pretrained-Language-Model/tree/master/NEZHA
• 自研语言模型: https://github.com/ZhuiyiTechnology/pretrained-models
• T5模型: https://github.com/google-research/text-to-text-transfer-transformer
• GPT2_ML: https://github.com/imcaspar/gpt2-ml
• Google原版ELECTRA: https://github.com/google-research/electra
• 哈工大版ELECTRA: https://github.com/ymcui/Chinese-ELECTRA
• CLUE版ELECTRA: https://github.com/CLUEbenchmark/ELECTRA

 

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

Attention

https://zhuanlan.zhihu.com/p/37601161

预训练在自然语言处理的发展: 从Word Embedding到BERT模型（ppt精简版）

https://mp.weixin.qq.com/s/LGJvvhotSg7XMn8mg3TZUw

【NLP】Attention原理和源码解析

https://zhuanlan.zhihu.com/p/43493999

BERT安装与使用

https://www.cnblogs.com/nxf-rabbit75/p/11938504.html