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Qtok: quality control tool for tokenization

Project description

Qtok: Quality Control Tool for Tokenizers

Qtok is a Python-based tool designed for quality control and analysis of tokenizers used in natural language processing (NLP) tasks.

Features

  • Analyze tokenizer vocabularies
  • Generate statistics on token distribution
  • Produce visualizations of token characteristics
  • Compare multiple tokenizers
  • Analyze Unicode coverage
  • Assess language-specific token distributions (Latin and Cyrillic scripts)

Installation

You can install Qtok using pip:

pip install qtok

Or clone the repository and install:

git clone https://github.com/nup-csai/Qtok.git
cd Qtok
pip install .

Usage

Qtok can be used as a command-line tool:

qtok -i /path/to/tokenizer.json -l tokenizer_label -o /path/to/output/folder

Arguments:

  • -i: Path to the tokenizer JSON file (required)
  • -l: Label for the tokenizer (optional, default is "default")
  • -o: Output folder for results (required)

Output

Qtok generates several output files:

  1. basic_stats.tsv and basic_stats.png: Basic statistics of the tokenizer
  2. unicode_stats.tsv and unicode_stats.png: Unicode coverage statistics
  3. latin_stats.tsv and latin_stats.png: Statistics for Latin script tokens
  4. cyrillic_stats.tsv and cyrillic_stats.png: Statistics for Cyrillic script tokens

Requirements

  • Python 3.6+
  • matplotlib
  • numpy
  • pandas

Contributing

Contributions to Qtok are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Authors

  • Aleksey Komissarov
  • Iaroslav Chelombitko
  • Egor Safronov

Contact

For any queries, please contact ad3002@gmail.com.

Acknowledgments

  • Thanks to all contributors and users of Qtok
  • Special thanks to the NLP community for inspiration and support

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