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Tokenization lies at the heart of natural language processing (NLP), serving as the critical first step in transforming raw, unstructured text into structured units that computational models can process. These units, known as tokens, are the foundation upon which tasks such as sentiment analysis, machine translation, text generation, and large-scale language modeling are built.

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Building a Tokenizer for the Transformers Architecture Model

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  • 发表日期：

    2026年

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  • Dilyan Grigorov

摘要

Tokenization lies at the heart of natural language processing (NLP), serving as the critical first step in transforming raw, unstructured text into structured units that computational models can process. These units, known as tokens, are the foundation upon which tasks such as sentiment analysis, machine translation, text generation, and large-scale language modeling are built.