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Sentencepiece

技能 已验证 活跃

Language-independent tokenizer treating text as raw Unicode. Supports BPE and Unigram algorithms. Fast (50k sentences/sec), lightweight (6MB memory), deterministic vocabulary. Used by T5, ALBERT, XLNet, mBART. Train on raw text without pre-tokenization. Use when you need multilingual support, CJK languages, or reproducible tokenization.

目的

To provide a fast, lightweight, and language-independent tokenizer for raw Unicode text, supporting BPE and Unigram algorithms for multilingual and CJK language processing.

功能

  • Language-independent tokenization of raw Unicode text
  • Support for BPE and Unigram tokenization algorithms
  • Fast (50k sentences/sec) and lightweight (6MB memory) performance
  • Deterministic vocabulary for reproducible tokenization
  • Examples for training, encoding, and decoding

使用场景

  • Building multilingual NLP models
  • Working with CJK languages
  • Ensuring reproducible tokenization across different environments
  • Training models directly on raw text without pre-tokenization

非目标

  • Providing a tokenizer for English-centric tasks specifically (though it can be used)
  • Acting as a wrapper for other tokenization libraries like HuggingFace Tokenizers or tiktoken
  • Offering complex pre-processing steps beyond basic Unicode normalization

安装

请先添加 Marketplace

/plugin marketplace add Orchestra-Research/AI-Research-SKILLs
/plugin install AI-Research-SKILLs@ai-research-skills

质量评分

已验证
98 /100
1 day ago 分析

信任信号

最近提交17 days ago
星标8.3k
许可证MIT
状态
查看源代码

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