A tokenizer tailored for the Kyrgyz language, now utilizing WordPiece segmentation to offer efficient, context-aware tokenization. Featuring a 100,000-subword vocabulary, this tokenizer is optimized for various Kyrgyz NLP tasks while maintaining robust linguistic coverage. Developed in collaboration with UlutSoft LLC, it reflects authentic Kyrgyz language usage. Features:
Language: Kyrgyz Vocabulary Size: 100,000 subwords Method: WordPiece
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.