| --- |
| license: mit |
| language: |
| - und |
| tags: |
| - tokenizer |
| - bpe |
| - flexitok |
| - fineweb2 |
| datasets: |
| - flexitok/mod-arithmetic |
| --- |
| |
| # Byte-Level BPE Tokenizer: numeric (100K) |
|
|
| 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 | 100,007 | |
| | Final Vocab Size | 100,007 | |
| | Pre-tokenizer | byte_level | |
| | Number handling | rtl_5digit | |
| | Contraction handling | False | |
| | Normalizer | NONE | |
| | Special Tokens | `<s>`, `</s>`, `<pad>`, `<unk>` | |
| | Training Shards | 1 | |
|
|
| ## Usage |
|
|
| ```python |
| from transformers import AutoTokenizer |
| |
| tokenizer = AutoTokenizer.from_pretrained("None") |
| tokens = tokenizer.encode("Hello, world!") |
| ``` |
|
|
| ## Files |
|
|
| - `tokenizer.json` — Full HuggingFace tokenizer |
| - `vocab.json` — Vocabulary mapping |
| - `merges.txt` — BPE merge rules |
|
|
| ## Sample Encoding |
| | Text | Tokens | Token IDs | |
| |------|--------|-----------| |
| | `123500119 mod 67` | `1235, 00, 119, , mod, , 67` | `2294, 87, 134, 6, 4, 6, 53` | |
|
|
