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https://blog.csdn.net/u012526436/article/details/93196139
XLNet 是一个类似 BERT 的模型，而不是完全不同的模型。总之，XLNET是一种通用的自回归预训练方法。它是CMU和Google Brain团队在2019年6月份发布的模型，最终，XLNet 在 20 个任务上超过了 BERT 的表现，并在 18 个任务上取得了当前最佳效果 1.
https://github.com/ymcui/Chinese-XLNet
Q: 训练XLNet花了多长时间？ A: XLNet-mid使用了Cloud TPU v3 (128G HBM)训练了2M steps（batch=32），大约需要3周时间。XLNet-base则是训练了4M steps。 Q: 为什么XLNet官方没有发布Multilingual或者Chinese XLNet？ A: （以下是个人看法）不得而知，很多人留言表示希望 …
https://proceedings.neurips.cc/paper/2019/file/dc6a7e655d7e5840e66733e9ee67cc69-Paper.pdf
XLNet, a generalized autoregressive method that leverages the best of both AR language modeling and AE while avoiding their limitations. Firstly, instead of using a fixed forward or backward factorization order as in conventional AR mod-els, XLNet maximizes the expected log likelihood of a sequence w.r.t. all possible permutations
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