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Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integrates seamlessly with transformers. Use when you need high-performance tokenization or custom tokenizer training.
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HuggingFace Tokenizers - Fast Tokenization for NLP
Fast, production-ready tokenizers with Rust performance and Python ease-of-use.
When to use HuggingFace Tokenizers
Use HuggingFace Tokenizers when:
Need extremely fast tokenization (<20s per GB of text) Training custom tokenizers from scratch Want alignment tracking (token → original text position) Building production NLP pipelines Need to tokenize large corpora efficiently
Performance :
Speed : <20 seconds to toke
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