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bpe_ltr_vie_Latn_4000_v2
flexitok/bpe_ltr_vie_Latn_4000_v2
bpe_ltr_vie_Latn_4000_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 vieLatn data from Fineweb-2-HQ.
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Public
Updated Apr 15, 2026
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At a glance
- License
- mit
- Access
- Public
- Created
- Apr 14, 2026
- Updated
- Apr 15, 2026
- SHA
- ccbe0435
Model card
From the Hugging Face model README
Byte-Level BPE Tokenizer: vie_Latn (4K)
A Byte-Level BPE tokenizer trained on vie_Latn data from Fineweb-2-HQ.
Training Details
| Parameter | Value |
|---|---|
| Algorithm | Byte-Level BPE |
| Language | vie_Latn |
| Target Vocab Size | 4,000 |
| Final Vocab Size | 5,034 |
| Pre-tokenizer | custom:vie_Latn |
| Number handling | ltr_3digit |
| 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_ltr_vie_Latn_4000_v2")
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, el, lo, ,, Ġw, orld, !, Ġ, 123, 45, ĠTh, is, Ġis, Ġa, Ġt, est, ., Ġ, ã, ģ | 42, 725, 1588, 14, 1262, 2592, 3, 223, 4638, 2735, 415, 783, 3017, 1671, 262, 1833, 16, 223, 162, 226 |
- License
- mit
- Languages
- vie
- Created
- Apr 14, 2026
- Updated
- Apr 15, 2026