XLNet is a language model designed for comprehensive language understanding. It utilizes a generalized autoregressive pretraining approach, which allows it to capture bidirectional dependencies in text data. Unlike traditional autoregressive models, XLNet considers all permutations of words in a sentence, enabling it to better understand the context and meaning of words. By training on large amounts of text data, XLNet learns to generate high-quality representations of language, making it suitable for various natural language processing tasks. Its advanced architecture ensures that it can effectively handle complex linguistic structures and nuances, providing accurate and reliable results across different domains and languages.
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