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flexitok/bpe_ltr_ind_Latn_32000_v2
bpe_ltr_ind_Latn_32000_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 indLatn 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 ind_Latn data from Fineweb-2-HQ.
| Parameter | Value |
|---|---|
| Algorithm | Byte-Level BPE |
| Language | ind_Latn |
| Target Vocab Size | 32,000 |
| Final Vocab Size | 32,851 |
| Pre-tokenizer | custom:ind_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_ind_Latn_32000_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, ello, ,, Ġworld, !, Ġ, 123, 45, ĠThis, Ġis, Ġa, Ġtest, ., Ġ, ãģ, ĵ, ãĤ, ĵ, ãģ, « | 42, 15107, 14, 16817, 3, 223, 17069, 4529, 13915, 1153, 395, 7029, 16, 223, 9732, 244, 15716, 244, 9732, 107 |