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feat2-bpe_tur_Latn_16000
flexitok/feat2-bpe_tur_Latn_16000
feat2-bpe_tur_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 turLatn data from Fineweb-2-HQ.
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Public
Updated Apr 9, 2026
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.json1.5 MB · 84%
At a glance
- License
- mit
- Access
- Public
- Created
- Apr 9, 2026
- Updated
- Apr 9, 2026
- SHA
- f455baf7
Model card
From the Hugging Face model README
Byte-Level BPE Tokenizer: tur_Latn (16K)
A Byte-Level BPE tokenizer trained on tur_Latn data from Fineweb-2-HQ.
Training Details
| Parameter | Value |
|---|---|
| Algorithm | Byte-Level BPE |
| Language | tur_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/feat2-bpe_tur_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, el, lo, ,, Ġw, orld, !, Ġ, 12, 3, 45, ĠT, his, Ġis, Ġa, Ġtest, ., Ġ, ãģ, ĵ | 43, 239, 1228, 15, 1085, 7548, 4, 177, 1270, 22, 3874, 335, 3309, 1065, 255, 1641, 17, 177, 5477, 197 |
- License
- mit
- Languages
- tur
- Created
- Apr 9, 2026
- Updated
- Apr 9, 2026