Скачать или смотреть 15. What is Tokenization? Why It’s Critical for Large Language Models (LLMs) | In Hindi

About this video: Ever wondered how an LLM actually "reads" your prompts? In this video, we break down Tokenization—the fundamental preprocessing step that converts raw text into meaningful units that AI can understand.

We dive deep into the technical necessity of tokenizing text, explaining how words, subwords, and characters are transformed into numerical representations.

What you will learn:

Defining Tokenization: The bridge between raw text and embedding vectors.

The Mechanics: How mapping tokens to numerical data allows models to learn semantic relationships and syntax.

Subword Advantage: Why subword tokenization is the secret to handling rare words, misspellings, and unseen vocabulary.

Performance Impact: How token counts (not word counts) determine your context window and computational efficiency.

Whether you're an AI researcher, a developer, or a student, understanding tokenization is key to mastering Large Language Models.

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