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bpe_ltr_ell_Grek_8000_v2
flexitok/bpe_ltr_ell_Grek_8000_v2
bpe_ltr_ell_Grek_8000_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 ellGrek data from Fineweb-2-HQ.
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Public
Updated Apr 18, 2026
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.json2.7 MB · 92%
At a glance
- License
- mit
- Access
- Public
- Created
- Apr 14, 2026
- Updated
- Apr 18, 2026
- SHA
- aec1b764
Model card
From the Hugging Face model README
Byte-Level BPE Tokenizer: ell_Grek (8K)
A Byte-Level BPE tokenizer trained on ell_Grek data from Fineweb-2-HQ.
Training Details
| Parameter | Value |
|---|---|
| Algorithm | Byte-Level BPE |
| Language | ell_Grek |
| Target Vocab Size | 8,000 |
| Final Vocab Size | 9,038 |
| Pre-tokenizer | custom:ell_Grek |
| 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_ell_Grek_8000_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, ell, o, ,, Ġ, w, or, ld, !, Ġ, 123, 45, Ġ, Th, is, Ġ, is, Ġ, a, Ġ | 42, 2576, 81, 14, 223, 89, 693, 5583, 3, 223, 8522, 4808, 223, 3829, 933, 223, 933, 223, 67, 223 |
- License
- mit
- Languages
- ell
- Created
- Apr 14, 2026
- Updated
- Apr 18, 2026