Skill · em Dados, IA e pesquisa
sentencepiece
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…
Procedência
- Origem: davila7/claude-code-templates
- Caminho:
cli-tool/components/skills/ai-research/tokenization-sentencepiece - Versão fixada:
57f899e5394bb8ca166f38eacae8f0853cbfe033 - Licença: MIT
- Espelhado em 25/09/2026
- nenhum download no Claude Code Templates (lido em 25/09/2026)
Antes de instalar
3 arquivos · 15,7 KB · só texto, nenhum script
Instalar na sua CLI
O comando baixa a versão fixada (commit 57f899e) direto da origem, para a pasta que a CLI lê. Precisa de curl (macOS e Linux); no Windows não há comando, porque o Rook Labs é para macOS.
Claude Code
Neste projeto: instala em .claude/skills/sentencepiece/.
d=".claude/skills/sentencepiece" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/tokenization-sentencepiece" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/algorithms.md" "$u/references/algorithms.md" \ -o "$d/references/training.md" "$u/references/training.md"
Global: instala em ~/.claude/skills/sentencepiece/.
d="$HOME/.claude/skills/sentencepiece" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/tokenization-sentencepiece" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/algorithms.md" "$u/references/algorithms.md" \ -o "$d/references/training.md" "$u/references/training.md"
Codex
Neste projeto: instala em .agents/skills/sentencepiece/.
d=".agents/skills/sentencepiece" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/tokenization-sentencepiece" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/algorithms.md" "$u/references/algorithms.md" \ -o "$d/references/training.md" "$u/references/training.md"
Global: instala em ~/.agents/skills/sentencepiece/.
d="$HOME/.agents/skills/sentencepiece" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/tokenization-sentencepiece" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/algorithms.md" "$u/references/algorithms.md" \ -o "$d/references/training.md" "$u/references/training.md"
Antigravity
Neste projeto: instala em .agents/skills/sentencepiece/.
d=".agents/skills/sentencepiece" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/tokenization-sentencepiece" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/algorithms.md" "$u/references/algorithms.md" \ -o "$d/references/training.md" "$u/references/training.md"
Global: instala em ~/.gemini/antigravity-cli/skills/sentencepiece/.
d="$HOME/.gemini/antigravity-cli/skills/sentencepiece" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/tokenization-sentencepiece" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/algorithms.md" "$u/references/algorithms.md" \ -o "$d/references/training.md" "$u/references/training.md"
Peça ao Rook
Já usa o Rook Labs? Cole no chat do Rook: instale a skill https://rooklabs.sh/marketplace/cct.sentencepiece
Prévia do SKILL.md
---
name: sentencepiece
description: 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…
version: 1.0.0
author: Orchestra Research
license: MIT
tags: [Tokenization, SentencePiece, Language-Independent, BPE, Unigram, Multilingual, CJK Languages, Unicode, Deterministic, Google]
dependencies: [sentencepiece, transformers]
---
# SentencePiece - Language-Independent Tokenization
Unsupervised tokenizer that works on raw text without language-specific preprocessing.
## When to use SentencePiece
**Use SentencePiece when:**
- Building multilingual models (no language-specific rules)
- Working with CJK languages (Chinese, Japanese, Korean)
- Need reproducible tokenization (deterministic vocabulary)
- Want to train on raw text (no pre-tokenization needed)
- Require lightweight deployment (6MB memory, 50k sentences/sec)
**Performance**:
- **Speed**: 50,000 sentences/sec
- **Memory**: ~6MB for loaded model
- **Languages**: All (language-independent)
**Use alternatives instead**:
- **HuggingFace Tokenizers**: Faster training, more flexibility
- **tiktoken**: OpenAI models (GPT-3.5/4)
- **BERT WordPiece**: English-centric tasks
## Quick start
### Installation
```bash
# Python
pip install sentencepiece
…