pipeline

Complete guide to normalizers, pre-tokenizers, models, post-processors, and decoders.

Skills
AI research
3

What it does and how to use it

A skill that teaches Claude Code to do ai research tasks well. It is packaged knowledge the model uses whenever it is relevant.

Install the skill (command above).
In Claude Code, describe what you need - the skill turns on by itself when the context fits.
No commands to memorize: you talk in plain language and the skill does the rest.

Install (Claude Code)

mkdir -p .claude/skills/pipeline && curl -fsSL https://doutorai.pt/data/lib/skills__pipeline.md -o .claude/skills/pipeline/SKILL.md

Paste this command into the terminal, in your project folder, and the component installs automatically.

Content

# Tokenization Pipeline Components

Complete guide to normalizers, pre-tokenizers, models, post-processors, and decoders.

## Pipeline overview

**Full tokenization pipeline**:
```
Raw Text
  ↓
Normalization (cleaning, lowercasing)
  ↓
Pre-tokenization (split into words)
  ↓
Model (apply BPE/WordPiece/Unigram)
  ↓
Post-processing (add special tokens)
  ↓
Token IDs
```

**Decoding reverses the process**:
```
Token IDs
  ↓
Decoder (handle special encodings)
  ↓
Raw Text
```

## Normalizers

Clean and standardize input text.

### Common normalizers

**Lowercase**:
```python
from tokenizers.normal

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