BART (Bidirectional and Auto-Regressive Transformer) is a sequence-to-sequence model primarily used for tasks like text generation, summarization, translation, and question answering. It is trained by corrupting text with an arbitrary noising function and then learning to reconstruct the original text. This makes it effective for both understanding and generating natural language.
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