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baby-tokenizer
nilq/baby-tokenizer
baby-tokenizer is a machine learning model from nilq. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
Compact sentencepiece tokenizer for sample-efficient English language modeling, simply tokenizing natural language.
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Public
Updated Feb 22, 2024
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At a glance
- License
- mit
- Access
- Public
- Created
- Jan 21, 2024
- Updated
- Feb 22, 2024
- SHA
- cc2d5e31
Datasets
Model card
From the Hugging Face model README
Baby Tokenizer
Compact sentencepiece tokenizer for sample-efficient English language modeling, simply tokenizing natural language.
Usage
Transformers
from transformers import AutoTokenizer
tokenizer_baby = AutoTokenizer.from_pretrained("nilq/baby-tokenizer")
Tokenizers
from tokenizers import Tokenizer
tokenizer_baby = Tokenizer.from_pretrained("nilq/baby-tokenizer")
Data
This tokeniser is derived from the BabyLM 100M dataset of mixed domain data, consisting of the following sources:
- CHILDES (child-directed speech)
- Subtitles (speech)
- BNC (speech)
- TED talks (speech)
- children's books (simple written language).
Specifications
- Vocabulary size: 20k
- Alphabet limit: 150
- Minimum token frequency: 100
- License
- mit
- Languages
- en
- Created
- Jan 21, 2024
- Updated
- Feb 22, 2024