🔤 Text Tokenization Playground
Break text into tokens for language models
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From Text to Numbers
Tokenization is the first step in NLP - breaking text into smaller units (tokens) that models can process. Each token gets converted to a number, creating the input for language models.
🎯 Why Tokenize?
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Convert to numbers: Models need numerical input
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Handle vocabulary: Manage fixed-size vocab
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Process efficiently: Enable batch processing
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Handle unknowns: Deal with rare words
🔄 Tokenization Pipeline
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Raw Text
"Hello world"
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Tokenize
["Hello", "world"]
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Convert
[1234, 5678]
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Model
Process tokens
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Vocabulary
Fixed set of all possible tokens (typically 10K-50K)
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Token IDs
Unique number assigned to each token
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UNK Token
Special token for unknown/rare words