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+ ---
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+ library_name: tokenizers
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+ tags:
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+ - tokenizer
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+ - multilingual
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+ - byte-level-bpe
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+ - indigenous-languages
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+ - tachiwin
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+ ---
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+
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+ # Tachiwin multilingual tokenizer
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+
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+ A multilingual ByteLevel-BPE tokenizer trained with Hugging Face Tokenizers.
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+
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+ ## Corpus weighting
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+
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+ | Component | Target |
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+ |---|---:|
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+ | Modern + old exotic-language data | 70% |
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+ | English | 10% |
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+ | Spanish | 10% |
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+ | Code | 10% |
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+
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+ The complete available exotic-language corpus is used as the 70% anchor.
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+ Its existing modern/old composition is preserved.
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+
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+ ## Tokenizer
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+
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+ - Model: BPE, trained via `Tokenizer.train_from_iterator` over a streaming
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+ line generator (constant memory regardless of corpus size)
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+ - Vocabulary target: 256,000
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+ - Initial alphabet: complete ByteLevel alphabet
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+ - ByteLevel GPT-2 regex: disabled
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+ - Unicode normalizer: none
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+ - Special tokens: 282
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+ - Human-language tags: 248
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+
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+ ## Corpus size
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+
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+ Total materialized corpus: 458,112,624 bytes (0.427 GiB)
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+
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+ ## Evaluation
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+
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+ The tokenizer was evaluated against the Tachiwin language catalogue.
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+ Languages without text samples are skipped. For each language, all
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+ available samples are concatenated ONLY within that language for aggregate
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+ fertility statistics. Metrics: characters/token, tokens/character, UTF-8
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+ bytes/token, tokens/UTF-8 byte, exact round-trip preservation.
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+
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+ ## Important training note
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+
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+ The Hugging Face BPE trainer does not expose an internal resumable
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+ merge-state checkpoint. The recipe therefore treats the completed
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+ `tokenizer.json` as the training checkpoint:
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+
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+ - corpus preparation is resumable (both the exotic streaming pass and the
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+ capped external-corpus downloads reuse existing shards);
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+ - recipe/statistics/checksums are stored in `recipe/`;
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+ - if `tokenizer.json` already exists, subsequent runs skip BPE training;
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+ - an interrupted BPE computation itself must be restarted.
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+
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+ ## Repository evaluation artifacts
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+
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+ - evaluation/catalogue.json
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+ - evaluation/language_fertility.csv
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+ - evaluation/language_fertility.json
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+ - evaluation/evaluation_summary.json