|
Download README.md from flexitok/bpe_fw_edu_4000_v2: direct link, hf CLI and curl.
- Browser
- Download file 1.27 kB
-
https://huggingface.co/flexitok/bpe_fw_edu_4000_v2/resolve/main/README.md
- Command line
-
hf download hf://flexitok/bpe_fw_edu_4000_v2/README.md
-
curl -L -o README.md https://huggingface.co/flexitok/bpe_fw_edu_4000_v2/resolve/main/README.md
1.27 kB
metadata
license: mit
language:
- fw
tags:
- tokenizer
- bpe
- flexitok
- fineweb2
Byte-Level BPE Tokenizer: fw_edu (4K)
A Byte-Level BPE tokenizer trained on fw_edu data from Fineweb-2-HQ.
Training Details
| Parameter | Value |
|---|---|
| Algorithm | Byte-Level BPE |
| Language | fw_edu |
| Target Vocab Size | 4,000 |
| Final Vocab Size | 4,000 |
| Pre-tokenizer | custom:fw_edu |
| 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_fw_edu_4000_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, ,, Ġworld, !, Ġ, 12, 3, 45, ĠThis, Ġis, Ġa, Ġtest, ., Ġ, ã, ģ, ĵ, ã |
43, 431, 82, 15, 858, 4, 178, 1046, 22, 3032, 609, 267, 214, 1028, 17, 178, 160, 180, 198, 160 |