flexitok/maddition_tur_Latn_2000

Byte-Level BPE Tokenizer: ['tur_Latn'] (2K)

A Byte-Level BPE tokenizer trained on ['tur_Latn'] data from Fineweb-2-HQ.

Training Details

Parameter	Value
Algorithm	Byte-Level BPE
Language	['tur_Latn']
Target Vocab Size	2,000
Final Vocab Size	318
Pre-tokenizer	custom:addition
Number handling	ltr_3digit
Contraction handling	False
Normalizer	NFC
Special Tokens	<s>, </s>, <pad>, <unk>
Training Shards	2

Usage

from transformers import AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("flexitok/maddition_tur_Latn_2000")
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
yirmi iki+dokuz=otuz bir\ntwenty two+nine=thirty one	yirmi, Ġ, iki, +, dokuz, =, otuz, Ġ, bir, \, n, t, w, e, n, t, y, Ġ, t, w	311, 223, 276, 13, 286, 31, 310, 223, 307, 62, 80, 86, 89, 71, 80, 86, 91, 223, 86, 89

Command used to create this tokenizer:

['/home/gsa/tokenizers2/flexitok/tokenizer_training/train_tokenizers.py', 'algorithm=bpe', 'vocab_size=2000', 'langs=[tur_Latn]', 'data_dir=/scratch/gsa/data/multilingual-addition/', 'output_dir=/scratch/gsa/trained_tokenizers/multilingual_addition', 'pretokenizer=custom:addition', 'number_handling=ltr_3digit', 'add_numbers=false', 'handle_contractions=false', 'unicode_normalization=nfc', 'use_byte_level_regex=false', 'byte_fallback=false', 'strip_zero_width=false', 'cjk_char_split=false', 'add_cjk_chars=false', 'max_lines=-1', 'test_string=yirmi iki+dokuz=otuz bir\\ntwenty two+nine=thirty one', 'hf.publish_to_hf=true', 'hf_repo_prefix=flexitok/', 'hf.hf_repo_id=flexitok/maddition_tur_Latn_2000', 'hf.collections=[flexitok/multilingual_addition_tokenizers]']