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license: mit
language:
- swe # ISO 639-3 code or "und" if not identifiable
tags:
- tokenizer
- bpe
- flexitok
- fineweb2
---
# Byte-Level BPE Tokenizer: swe_Latn (16K)
A **Byte-Level BPE** tokenizer trained on **swe_Latn** data from Fineweb-2-HQ.
## Training Details
| Parameter | Value |
|-----------|-------|
| Algorithm | Byte-Level BPE |
| Language | `swe_Latn` |
| Target Vocab Size | 16,000 |
| Final Vocab Size | 16,965 |
| Pre-tokenizer | custom:swe_Latn |
| Number handling | ltr_3digit |
| Contraction handling | True |
| Normalizer | NFC |
| Special Tokens | `<s>`, `</s>`, `<pad>`, `<unk>` |
| Training Shards | 2 |
## Usage
```python
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("flexitok/bpe_ltr_swe_Latn_16000_v2")
tokens = tokenizer.encode("Hello, world!")
```
## Files
- `tokenizer.json` — Full HuggingFace tokenizer
- `vocab.json` — Vocabulary mapping
- `merges.txt` — BPE merge rules
## Sample Encoding
| Text | Tokens | Token IDs |
|------|--------|-----------|
| `Hello, world! 12345 This is a test. こんにちは` | `H, ell, o, ,, Ġw, orld, !, Ġ, 123, 45, ĠTh, is, Ġis, Ġa, Ġtest, ., Ġ, ãģ, ĵ, ã` | `42, 468, 81, 14, 744, 4856, 3, 223, 16116, 4268, 1345, 359, 1677, 271, 2233, 16, 223, 10365, 244, 162` |
|