Designing a transformer-based chatbot involves a series of intricate steps, serving as the foundation for effective conversational AI. It begins with data collection and preprocessing, where the chatbot learns from conversation examples, understands user queries, and delivers relevant responses. The model employs tokenization to break down text data into manageable units. At its core, the transformer architecture, comprising encoder–decoder components, powers the chatbot.
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