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tokenizers

huggingface/tokenizers

💥 Fast State-of-the-Art Tokenizers optimized for Research and Production

GitHub Website

GraphCanon updated 2w · GitHub synced 2w

11k stars1.2k forksLast push 2w Rust Apache-2.0

Decision brief

Factual criteria for evaluating 'tokenizers'.

Good fit when

When you require a library that is optimized both for research and production environments, ensuring efficiency in NLP tasks.
For projects involving state-of-the-art models like BERT or GPT where the performance of tokenization can have a significant impact on model training speed.

Avoid when

If your project is limited to older NLP models which do not require such advanced tokenizers, opting for something simpler might be more appropriate.
In scenarios where Rust-based tooling does not fit within your existing tech stack and there's no immediate plan or capability to integrate new languages.

Pricing:: freemium
Requirements:: Min 4 GB RAM; Installation can be done directly via pip or from source, offering flexibility for different project needs.

Observed Jul 12, 2026 · Source: enrich:decision_facts

tokenizers alternatives Trust report

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Maintenance and security

Full trust report

Maintenance: Very active (0d since push); As of 2w
Provenance: Not a fork · Organization account; As of 2w
Security (OSV): No lockfile; As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Backing

Company context for Hugging Face. Display-only - separate from trust and ranking.

Company: Hugging Face·GitHub org profile·1mo
Employees: 160·Wikidata (P1128 employees)·1mo
Funding: $235,000,000 (2023-08)·GraphCanon curated seed (public press)·1mo
Commercial model: OSS + managed cloud·GraphCanon curated seed·1mo

Install

cargo add tokenizers

crates.io

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

A library of fast and efficient state-of-the-art tokenizers, vital for tasks in natural language processing, including training models like BERT and GPT.

Capability facts

Languages: rust
Source: github.language · Aug 2, 2026

Graph entities

Hugging Facecompany

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Aug 2, 2026)

install git+https://github.com/huggingface/tokenizers.git#subdirectory=bindings/python

Source link

README

Installation

You can install from source using:

pip install git+https://github.com/huggingface/tokenizers.git#subdirectory=bindings/python

or install the released versions with

pip install tokenizers

For agents

This page has a .md twin and JSON over the API.

/tools/huggingface-tokenizers.md GET /api/graphcanon/tools/huggingface-tokenizers GET /api/graphcanon/graph?tool=huggingface-tokenizers