Tokenization is a crucial step in natural language processing (NLP), where we break down text into smaller units (tokens) for further analysis. In this article, we’ll explore various tokenization techniques, their pros and cons, and practical tips for implementing them in Python.
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Contents
1. Introduction to Tokenization
2. Basic Tokenization Techniques
3. Advanced Tokenization Methods
4. Handling Special Cases
5. Tokenization in Pretrained LLMs
6. Tips for Efficient Tokenization
1. Introduction to Tokenization
In this section, we’ll explore the basics of tokenization, its importance for large language models (LLMs), and the difference between tokenization and word segmentation.
