pyrwkv-tokenizer

Name	pyrwkv-tokenizer JSON
Version	0.9.0 JSON
	download
home_page	None
Summary	RWKV Tokenizer
upload_time	2024-08-16 11:36:23
maintainer	None
docs_url	None
author	Cahya Wirawan <cahya.wirawan@gmail.com>
requires_python	>=3.8
license	Apache-2.0
keywords	llm rwkv language model
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # RWKV Tokenizer

[![GitHub Actions Status](https://github.com/cahya-wirawan/rwkv-tokenizer/actions/workflows/CI.yml/badge.svg)](https://github.com/cahya-wirawan/rwkv-tokenizer/actions/)
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A fast RWKV Tokenizer written in Rust that supports the World Tokenizer used by the 
[RWKV](https://github.com/BlinkDL/RWKV-LM) v5 and v6 models.

## Installation
Install the rwkv-tokenizer python module:
```
$ pip install pyrwkv-tokenizer
```
## Usage
```
>>> import pyrwkv_tokenizer
>>> tokenizer = pyrwkv_tokenizer.RWKVTokenizer()
>>> tokenizer.encode("Today is a beautiful day. 今天是美好的一天。")
[33520, 4600, 332, 59219, 21509, 47, 33, 10381, 11639, 13091, 15597, 11685, 14734, 10250, 11639, 10080]
>>> tokenizer.decode([33520, 4600, 332, 59219, 21509, 47, 33, 10381, 11639, 13091, 15597, 11685, 14734, 10250, 11639, 10080])
'Today is a beautiful day. 今天是美好的一天。'

```

## Performance and Validity Test

We compared the encoding results of the Rust RWKV Tokenizer and the original tokenizer using
the English Wikipedia and Chinese poetries datasets. Both results are identical. The Rust RWKV Tokenizer also 
passes [the original tokenizer's unit test](https://github.com/BlinkDL/ChatRWKV/blob/main/tokenizer/rwkv_tokenizer.py). 
The following steps describe how to do the unit test:
```
$ pip install pytest pyrwkv-tokenizer
$ git clone https://github.com/cahya-wirawan/rwkv-tokenizer.git
$ cd rwkv-tokenizer
$ pytest
```

We did a performance comparison on [the simple English Wikipedia dataset 20220301.en](https://huggingface.co/datasets/legacy-datasets/wikipedia) among following tokenizer:
- The original RWKV tokenizer (BlinkDL)
- Huggingface implementaion of RWKV tokenizer
- Huggingface LLama tokenizer
- Huggingface Mistral tokenizer
- Bert tokenizer
- OpenAI Tiktoken
- The Rust RWKV tokenizer

The comparison is done using this [jupyter notebook](https://github.com/cahya-wirawan/rwkv-tokenizer/blob/main/tools/rwkv_tokenizers.ipynb) in a M2 Mac mini. The Rust RWKV 
tokenizer is around 17x faster than the original tokenizer and 9.6x faster than OpenAI Tiktoken.

![performance-comparison](https://media.githubusercontent.com/media/cahya-wirawan/rwkv-tokenizer/main/data/performance-comparison.png)

## Bugs
~~There are still bugs where some characters are not encoded correctly.~~ The bug have been fixed in the version 0.3.0.
*This tokenizer is my very first Rust program, so it might still have many bugs and silly codes :-)*

            

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    "description": "# RWKV Tokenizer\n\n[![GitHub Actions Status](https://github.com/cahya-wirawan/rwkv-tokenizer/actions/workflows/CI.yml/badge.svg)](https://github.com/cahya-wirawan/rwkv-tokenizer/actions/)\n[![Pypi.org Version](https://img.shields.io/pypi/v/pyrwkv-tokenizer.svg)](https://pypi.org/project/pyrwkv-tokenizer/)\n[![Pypi.org Downloads](https://img.shields.io/pypi/dd/pyrwkv-tokenizer)](https://pypi.org/project/pyrwkv-tokenizer/)\n[![License: Apache 2.0](https://img.shields.io/badge/license-Apache_2.0-blue.svg)](https://github.com/cahya-wirawan/rwkv-tokenizer/blob/main/LICENSE.txt)\n\n\nA fast RWKV Tokenizer written in Rust that supports the World Tokenizer used by the \n[RWKV](https://github.com/BlinkDL/RWKV-LM) v5 and v6 models.\n\n## Installation\nInstall the rwkv-tokenizer python module:\n```\n$ pip install pyrwkv-tokenizer\n```\n## Usage\n```\n>>> import pyrwkv_tokenizer\n>>> tokenizer = pyrwkv_tokenizer.RWKVTokenizer()\n>>> tokenizer.encode(\"Today is a beautiful day. \u4eca\u5929\u662f\u7f8e\u597d\u7684\u4e00\u5929\u3002\")\n[33520, 4600, 332, 59219, 21509, 47, 33, 10381, 11639, 13091, 15597, 11685, 14734, 10250, 11639, 10080]\n>>> tokenizer.decode([33520, 4600, 332, 59219, 21509, 47, 33, 10381, 11639, 13091, 15597, 11685, 14734, 10250, 11639, 10080])\n'Today is a beautiful day. \u4eca\u5929\u662f\u7f8e\u597d\u7684\u4e00\u5929\u3002'\n\n```\n\n## Performance and Validity Test\n\nWe compared the encoding results of the Rust RWKV Tokenizer and the original tokenizer using\nthe English Wikipedia and Chinese poetries datasets. Both results are identical. The Rust RWKV Tokenizer also \npasses [the original tokenizer's unit test](https://github.com/BlinkDL/ChatRWKV/blob/main/tokenizer/rwkv_tokenizer.py). \nThe following steps describe how to do the unit test:\n```\n$ pip install pytest pyrwkv-tokenizer\n$ git clone https://github.com/cahya-wirawan/rwkv-tokenizer.git\n$ cd rwkv-tokenizer\n$ pytest\n```\n\nWe did a performance comparison on [the simple English Wikipedia dataset 20220301.en](https://huggingface.co/datasets/legacy-datasets/wikipedia) among following tokenizer:\n- The original RWKV tokenizer (BlinkDL)\n- Huggingface implementaion of RWKV tokenizer\n- Huggingface LLama tokenizer\n- Huggingface Mistral tokenizer\n- Bert tokenizer\n- OpenAI Tiktoken\n- The Rust RWKV tokenizer\n\nThe comparison is done using this [jupyter notebook](https://github.com/cahya-wirawan/rwkv-tokenizer/blob/main/tools/rwkv_tokenizers.ipynb) in a M2 Mac mini. The Rust RWKV \ntokenizer is around 17x faster than the original tokenizer and 9.6x faster than OpenAI Tiktoken.\n\n![performance-comparison](https://media.githubusercontent.com/media/cahya-wirawan/rwkv-tokenizer/main/data/performance-comparison.png)\n\n## Bugs\n~~There are still bugs where some characters are not encoded correctly.~~ The bug have been fixed in the version 0.3.0.\n*This tokenizer is my very first Rust program, so it might still have many bugs and silly codes :-)*\n",
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