NIRVLab — BPE Tokenizer for Turkish XNLI

A Byte-Pair Encoding (BPE) tokenizer trained from scratch on the Turkish (tr) subset of the facebook/xnli dataset.

Training Details

Parameter Value
Algorithm BPE (ByteLevel)
Vocabulary size 8,000
Min frequency 2
Special tokens <s>, <pad>, </s>, <unk>, <mask>
Corpus facebook/xnli / tr — all splits
Corpus size 800,404 sentences
Normalizer NFC Unicode
Pre-tokenizer ByteLevel

Evaluation Metrics

Metric Value
Tokens / char 0.2581
Fertility (tokens / word) 1.9330
Avg sequence length 20.15 tokens
Vocabulary coverage 1.0000

Usage

from transformers import AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("NIRVLab/xnli-bpe-tr")
tokens = tokenizer("Merhaba dünya!", return_tensors="pt")
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Dataset used to train NIRVLab/xnli-bpe-tr