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Alright, let's start with the basics. Imagine you have a sentence like, "The quick brown rabbit jumps over the lazy frogs." A tokenizer's job is to take that sentence and break it down into smaller units called **tokens**. These tokens can be words, parts of words (like "ing" or "un-"), or even punctuation marks. Why is this important? Because computers don't understand human language directly. They need to work with numbers. Tokenization is the process of converting text into a numerical format that a computer can understand and process. This conversion allows the language models to analyze the text. It allows the machine learning model to understand the context and relationships between words, which is essential for tasks like:
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