xlnet

The XLNet model is an extension of the Transformer-XL model that is pre-trained using an autoregressive method to learn bidirectional contexts. It was proposed in the paper 'XLNet: Generalized Autoregressive Pretraining for Language Understanding' by Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, and Quoc V. Le. XLNet can be used for a wide range of natural language processing tasks, including text classification, machine translation, text generation, and question answering.