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flexitok/bpe_ltr_swe_Latn_1000_v2
bpe_ltr_swe_Latn_1000_v2 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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Updated Apr 15, 2026
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From the Hugging Face model README
A Byte-Level BPE tokenizer trained on swe_Latn data from Fineweb-2-HQ.
| Parameter | Value |
|---|---|
| Algorithm | Byte-Level BPE |
| Language | swe_Latn |
| Target Vocab Size | 1,000 |
| Final Vocab Size | 2,096 |
| Pre-tokenizer | custom:swe_Latn |
| Number handling | ltr_3digit |
| Contraction handling | True |
| Normalizer | NFC |
| Special Tokens | <s>, </s>, <pad>, <unk> |
| Training Shards | 2 |
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("flexitok/bpe_ltr_swe_Latn_1000_v2")
tokens = tokenizer.encode("Hello, world!")
tokenizer.json — Full HuggingFace tokenizervocab.json — Vocabulary mappingmerges.txt — BPE merge rules| Text | Tokens | Token IDs |
|---|---|---|
Hello, world! 12345 This is a test. こんにちは | H, ell, o, ,, Ġw, or, ld, !, Ġ, 123, 45, ĠT, h, is, Ġi, s, Ġa, Ġt, est, . | 42, 468, 81, 14, 744, 290, 675, 3, 223, 1062, 2085, 404, 74, 359, 296, 85, 271, 276, 522, 16 |