# Tokenizer

## Recommended Tokenizer

Use a byte-level BPE tokenizer with explicit FIM and metadata tokens. The
current local tokenizer uses Hugging Face `tokenizers` JSON format.

Required special tokens:

- `<|fim_prefix|>`
- `<|fim_suffix|>`
- `<|fim_middle|>`
- `<|fim_pad|>`
- `<|repo|>`
- `<|file|>`
- `<|lang|>`
- `<|endoftext|>`
- `<|pad|>`

## Usage Rules

- Encode with `add_special_tokens=False` when the record text already contains
  FIM markers.
- Decode audits with `skip_special_tokens=False`.
- Preserve indentation, tabs, newlines, comments, and Korean text.
- Do not lowercase or normalize code whitespace.
- Append EOS between JSONL records during training.

## Quality Checks

Audit tokenizer quality with:

- Special tokens remain atomic.
- Round-trip decode has no byte loss.
- FIM markers remain visible in decoded samples.
- Code chars/token is stable across Python, Rust, C++, JavaScript, and Java.