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nazrinburz/azerbaijani-sentencepiece-tokenizer
azerbaijani-sentencepiece-tokenizer is a machine learning model from nazrinburz. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
This repository provides a SentencePiece tokenizer trained for the Azerbaijani language. It uses a Byte-Pair Encoding (BPE) model trained with SentencePiece and wrapped as a Hugging Face T5TokenizerFast object for eas…
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Updated Sep 1, 2025
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From the Hugging Face model README
This repository provides a SentencePiece tokenizer trained for the Azerbaijani language. It uses a Byte-Pair Encoding (BPE) model trained with SentencePiece and wrapped as a Hugging Face T5TokenizerFast object for easy integration with the 🤗 Transformers ecosystem.
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
Preprocessing Azerbaijani text for NLP tasks
from transformers import AutoTokenizer
# Load tokenizer from the Hub
tokenizer = AutoTokenizer.from_pretrained("nazrinburz/azerbaijani-sentencepiece-tokenizer")
# Example text in Azerbaijani
text = "Azərbaycan dilinin inkişafı mədəniyyətimizin qorunması və gələcək nəsillərə ötürülməsi üçün vacib şərtdir."
# Tokenize
tokens = tokenizer.tokenize(text)
print("Tokens:", tokens)
# Encode into IDs
ids = tokenizer.encode(text)
print("Token IDs:", ids)
# Decode back to text
decoded = tokenizer.decode(ids)
print("Decoded:", decoded)