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๐Ÿ“Š Topic 04: Tokenization โ€” Text Ko Numbers Me Badalna

Course: LLM Engineering โ€” Hinglish Section: 1 โ€” LLM Foundations Level: Beginner โ†’ Intermediateโ€ฆ

Overview
๐ŸŒŸ

๐Ÿ“Š Topic 04: Tokenization โ€” Text Ko Numbers Me Badalna โ€” Quick Facts

๐Ÿ“Œ

Feature: BPE (GPT)

๐ŸŽฏ

Base Unit: Byte pairs

โšก

Prefix: Space before word

๐Ÿ”‘

Pre-tokenize: Whitespace split

Topic 1
โœจ

๐Ÿ“Œ Objectives

๐Ÿ’ก

Tokenization kya hai aur kyunโ€ฆ

๐Ÿ”‘

BPE, WordPiece, SentencePieceโ€ฆ

โšก

Different tokenizers ka comparisonโ€ฆ

๐ŸŽฏ

Token counting aur cost estimationโ€ฆ

Topic 2
โœจ

๐Ÿง  1. Tokenization Kya Hai?

๐Ÿ’ก LLM sirf numbers samajhta hai. Text ko numbers me convert karne ka process tokenizationโ€ฆ
Topic 3
๐Ÿ“ฅ โš™๏ธ ๐Ÿ”ฌ ๐Ÿ’ก

๐Ÿ”ค 2. BPE โ€” Byte Pair Encoding

๐Ÿ’ก

Greedy algorithm โ€” Har step meโ€ฆ

๐Ÿ”‘

Vocabulary size fixed โ€” 32K, 50K,โ€ฆ

โšก

Common words โ†’ single token ("the"โ€ฆ

๐ŸŽฏ

Rare words โ†’ multiple subwordโ€ฆ

Topic 4
โœจ

๐Ÿงฉ 3. Tokenizer Comparison

โญ | Feature | BPE (GPT) | WordPiece (BERT) | SentencePiece (T5, Gemma) | Tiktoken (OpenAI)โ€ฆ
Topic 5
โœจ

๐Ÿ’ฐ 4. Token Cost & Economics

๐Ÿ”‘ ` โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ TOKEN ECONOMICS (2024-2025)โ€ฆ
Topic 6
โœจ ๐Ÿ“Š ๐Ÿ”ฌ

๐Ÿ”ข 5. Special Tokens

โœจ ` โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ SPECIAL TOKENS โ”‚โ€ฆ
Topic 7
โœจ

๐Ÿ’ป 6. Python Code โ€” Complete Tokenizer System

๐Ÿ’ก

Token count

๐Ÿ”‘

Compression ratio

โšก

Cost estimate

๐ŸŽฏ

Language-based analysis

Topic 8
๐Ÿš€

๐Ÿ”ฌ 7. Tokenization Pitfalls

๐Ÿš€ 7.1 Common Problems: ` โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚โ€ฆ
Topic 9
โœจ

โ“ 8. Quiz โ€” 5 MCQs

๐Ÿ’ก

a) Random pairs merge karna

๐Ÿ”‘

b) Most frequent adjacent pairโ€ฆ

โšก

c) Longest word pehle tokenizeโ€ฆ

๐ŸŽฏ

d) Alphabetical order me splitโ€ฆ

Topic 10
โœจ

๐Ÿ”— Navigation

๐Ÿ’ก | โฌ…๏ธ Previous | ๐Ÿ“š Index | โžก๏ธ Next | |---|---|---| | 03-LLM-Architecture.md | 00-Index.mdโ€ฆ
Comparison
โœจ

๐Ÿงฉ 3. Tokenizer Comparison

โš–๏ธ

Base Unit: Byte pairs

โš–๏ธ

Prefix: Space before word

โš–๏ธ

Pre-tokenize: Whitespace split

Quick Quiz
๐Ÿง  QUIZ TIME

Quiz โ€” Question 1

๐Ÿ“Š Topic 04: Tokenization โ€” Text Ko Numbers Me Badalna ka sabse sahi definition kya hai?

Quick Quiz
๐Ÿง  QUIZ TIME

Quiz โ€” Question 2

๐Ÿ“Š Topic 04: Tokenization โ€” Text Ko Numbers Me Badalna ka 'Base Unit' kya hai?

Complete! ๐ŸŽ‰
COMPLETE

๐Ÿ“Š Topic 04: Tokenization โ€” Text Ko Numbers Me Badalna Complete!

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