A basic Byte Pair Encoding (BPE) tokenizer implemented in Rust. This project provides a foundational implementation for tokenizing text using custom merge operations and vocabulary management. It is designed to be modular, efficient, and easily extendable for industry-grade NLP applications.
- Basic BPE Implementation: Encode text into token IDs and decode them back to strings.
- Custom Vocabulary & Merges: Dynamically build vocabularies and define merge rules.
- Error Handling: Basic error management for out-of-vocabulary tokens and token ID mismatches.
- Modular Structure: Separated modules for models, training, and error definitions.
- Testing: Includes unit and integration tests to ensure basic functionality.
- Rust (Edition 2021 or later)
- Cargo (Rust’s package manager)
Clone the repository and build the project:
git clone https://github.com/yourusername/rust_tokenizer.git
cd rust_tokenizer/bpe
cargo buildRun the basic implementation:
cargo testThis command executes all unit and integration tests, validating the functionality of the tokenizer.
We have outlined several phases for further development:
- Phase 1: Basic Functionality
- Finalize and optimize the current implementation.
- Expand unit and integration tests.
- Phase 2: Enhanced Error Handling
- Implement robust error handling for edge cases.
- Improve logging and detailed error messages.
- Phase 3: Advanced Tokenization Techniques
- Extend the trainer with more sophisticated BPE algorithms.
- Introduce support for subword tokenization and dynamic vocabulary management.
- Phase 4: Industry-Ready Features
- Optimize performance for large-scale corpora.
- Benchmark performance and integrate with popular NLP pipelines.
Contributions are welcome! Please see the CONTRIBUTING.md file for guidelines on how to get involved.
For any inquiries or feedback, please contact me at b22cs089@iitj.ac.in.