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XLM (Cross-lingual Language Model) is a type of pretrained neural network model designed to understand and generate text across multiple languages. It leverages multilingual training data to improve performance on various natural language processing tasks involving different languages.
mT5 is a multilingual variant of the T5 (Text-to-Text Transfer Transformer) model developed by Google Research to support natural language processing tasks across multiple languages using a unified framework.
ByT5 is a transformer-based model designed for natural language processing tasks that operates directly on byte-level input rather than traditional tokenized text. It aims to improve language understanding across multiple languages and domains by avoiding tokenization issues.