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bpe_ell_Grek_4000
flexitok/bpe_ell_Grek_4000
bpe_ell_Grek_4000 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 11, 2026
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.json450 KB · 82%
At a glance
- License
- mit
- Access
- Public
- Created
- Apr 11, 2026
- Updated
- Apr 11, 2026
- SHA
- c1908ccb
Model card
From the Hugging Face model README
Byte-Level BPE Tokenizer: ell_Grek (4K)
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 | 4,000 |
| Final Vocab Size | 4,000 |
| 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/-bpe_ell_Grek_4000")
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, ,, Ġw, or, l, d, !, Ġ, 12, 3, 4, 5, ĠT, h, is, Ġ, is, Ġa | 43, 2571, 82, 15, 1793, 650, 79, 71, 4, 177, 1549, 22, 23, 24, 753, 75, 901, 177, 901, 2841 |
- License
- mit
- Languages
- ell
- Created
- Apr 11, 2026
- Updated
- Apr 11, 2026