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bpe_swe_Latn_16000
flexitok/bpe_swe_Latn_16000
bpe_swe_Latn_16000 is a machine learning model from flexitok. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
A Byte-Level BPE tokenizer trained on sweLatn data from Fineweb-2-HQ.
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Public
Updated Apr 10, 2026
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.json1.4 MB · 85%
At a glance
- License
- mit
- Access
- Public
- Created
- Feb 22, 2026
- Updated
- Apr 10, 2026
- SHA
- c215a666
Model card
From the Hugging Face model README
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 | 16,000 |
| Pre-tokenizer | gpt4 |
| Number handling | individual |
| Contraction handling | True |
| Normalizer | NFC |
| Special Tokens | <s>, </s>, <pad>, <unk> |
| Training Shards | 2 |
Usage
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("flexitok/-bpe_swe_Latn_16000")
tokens = tokenizer.encode("Hello, world!")
Files
tokenizer.json— Full HuggingFace tokenizervocab.json— Vocabulary mappingmerges.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, 12, 3, 45, ĠTh, is, Ġis, Ġa, Ġtest, ., Ġ, ãģ, ĵ | 43, 421, 82, 15, 698, 4836, 4, 176, 1502, 22, 4253, 1302, 312, 1639, 223, 2195, 17, 176, 10380, 196 |
- License
- mit
- Languages
- swe
- Created
- Feb 22, 2026
- Updated
- Apr 10, 2026