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mod-tokenizers-zero-padded-rtl_2digit
flexitok/mod-tokenizers-zero-padded-rtl_2digit
mod-tokenizers-zero-padded-rtl_2digit 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 numeric data from Fineweb-2-HQ.
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At a glance
- License
- mit
- Model type
- llama
- Access
- Public
- Created
- Mar 3, 2026
- Updated
- Mar 4, 2026
- SHA
- 292f0cda
Datasets
Model card
From the Hugging Face model README
Byte-Level BPE Tokenizer: numeric (0K)
A Byte-Level BPE tokenizer trained on numeric data from Fineweb-2-HQ.
Training Details
| Parameter | Value |
|---|---|
| Algorithm | Byte-Level BPE |
| Language | numeric |
| Target Vocab Size | 116 |
| Final Vocab Size | 107 |
| Pre-tokenizer | byte_level |
| Number handling | rtl_2digit |
| Contraction handling | False |
| Normalizer | NONE |
| Special Tokens | <s>, </s>, <pad>, <unk> |
| Training Shards | 1 |
Usage
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("None")
tokens = tokenizer.encode("Hello, world!")
Files
tokenizer.json— Full HuggingFace tokenizervocab.json— Vocabulary mappingmerges.txt— BPE merge rules
Sample Encoding
| Text | Tokens | Token IDs |
|---|---|---|
103500109 mod 67 | 1, 0, 3, 50, 0, 1, 0, 9, , mod, , 67 | 8, 7, 10, 57, 7, 8, 7, 16, 6, 4, 6, 74 |
- Type
- llama
- License
- mit
- Languages
- und
- Created
- Mar 3, 2026
- Updated
- Mar 4, 2026