A tokenizer tailored for the Kyrgyz language, utilizing SentencePiece with Byte Pair Encoding (BPE) to offer efficient and precise tokenization. It features a 150,000-subword vocabulary, ensuring optimal performance for various Kyrgyz NLP tasks. This tokenizer was developed in collaboration with UlutSoft LLC to reflect authentic Kyrgyz language usage.
Language: Kyrgyz Vocabulary Size: 150,000 subwords Method: SentencePiece (BPE)
Applications: Data preparation for language models, machine translation, sentiment analysis, chatbots. Usage Example (Python with transformers):
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("Your/Tokenizer/Path")
text = "Кыргыз тили – бай жана кооз тил."
tokens = tokenizer(text)
print(tokens)
Tip: Consider applying normalization or lemmatization during preprocessing to further enhance the results.
License and Attribution This tokenizer is licensed under the MIT License and was developed in collaboration with UlutSoft LLC. Proper attribution is required when using this tokenizer or derived resources.
Feedback and Contributions We welcome feedback, suggestions, and contributions! Please open an issue or a pull request in the repository to help us refine and enhance this resource.