tocount 0.2

ToCount: Lightweight Token Estimator

ToCount: Lightweight Token Estimator

---

Overview

ToCount is a lightweight and extensible Python library for estimating token counts from text inputs using both rule-based and machine learning methods. Designed for flexibility, speed, and accuracy, ToCount provides a unified interface for different estimation strategies, making it ideal for tasks like prompt analysis, token budgeting, and optimizing interactions with token-based systems.

PyPI Counter
Github Stars

Branch	main	dev
CI

Installation

PyPI

• Check Python Packaging User Guide
• Run pip install tocount==0.2

Source code

• Download Version 0.2 or Latest Source
• Run pip install .

Models

Rule-Based

Model Name	MAE	MSE	R²
RULE_BASED.UNIVERSAL	106.70	381,647.81	0.8175
RULE_BASED.GPT_4	152.34	571,795.89	0.7266
RULE_BASED.GPT_3_5	161.93	652,923.59	0.6878

Tiktoken R50K

Model Name	MAE	MSE	R²
TIKTOKEN_R50K.LINEAR_ALL	71.38	183897.01	0.8941
TIKTOKEN_R50K.LINEAR_ENGLISH	23.35	14127.92	0.9887

ℹ️ The training and testing dataset is taken from Lmsys-chat-1m [1] and Wildchat [2].

Usage

>>> from tocount import estimate_text_tokens, TextEstimator
>>> estimate_text_tokens("How are you?", estimator=TextEstimator.RULE_BASED.UNIVERSAL)
4

Issues & bug reports

Just fill an issue and describe it. We'll check it ASAP! or send an email to [e-mail].

• Please complete the issue template

You can also join our discord server

References

1- Zheng, Lianmin, et al. "Lmsys-chat-1m: A large-scale real-world llm conversation dataset." International Conference on Learning Representations (ICLR) 2024 Spotlights.

2- Zhao, Wenting, et al. "Wildchat: 1m chatgpt interaction logs in the wild." International Conference on Learning Representations (ICLR) 2024 Spotlights.

Show your support

Star this repo

Give a ⭐️ if this project helped you!

Donate to our project

If you do like our project and we hope that you do, can you please support us? Our project is not and is never going to be working for profit. We need the money just so we can continue doing what we do ;-) .

Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog and this project adheres to Semantic Versioning.

Unreleased

0.2 - 2025-10-02

Added

• TIKTOKEN_R50K.LINEAR_ALL model
• TIKTOKEN_R50K.LINEAR_ENGLISH model

Changed

• README.md updated

0.1 - 2025-08-30

Added

• RULE_BASED.UNIVERSAL model
• RULE_BASED.GPT_4 model
• RULE_BASED.GPT_3_5 model