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README.md
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---
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license: mit
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language:
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- en
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tags:
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- babylm
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- tokenizer
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datasets:
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- nilq/babylm-100M
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---
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## Baby Tokenizer (Uncased)
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Compact sentencepiece tokenizer for sample-efficient English language modeling, simply tokenizing natural language.
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### Usage
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#### Transformers
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```py
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from transformers import AutoTokenizer
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tokenizer_baby = AutoTokenizer.from_pretrained("nilq/baby-tokenizer")
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```
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#### Tokenizers
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```py
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from tokenizers import Tokenizer
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tokenizer_baby = Tokenizer.from_pretrained("nilq/baby-tokenizer")
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```
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### Data
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This tokeniser is derived from the BabyLM 100M dataset of mixed domain data, consisting of the following sources:
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- CHILDES (child-directed speech)
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- Subtitles (speech)
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- BNC (speech)
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- TED talks (speech)
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- children's books (simple written language).
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### Specifications
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- Vocabulary size: 20k
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- Alphabet limit: 150
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- Minimum token frequency: 100
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