xlnet
XLNet: Generalized Autoregressive Pretraining for Language Understanding
What is 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.
Key Features and Benefits
- Autoregressive pretraining to learn bidirectional contexts.
- Support for a wide range of natural language processing tasks.
- State-of-the-art performance on various benchmarks.
- Robust and efficient implementation.
Use Cases
- Text classification.
- Machine translation.
- Text generation.
- Question answering.
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