CCRss
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tokenizer_t5_kz

text-generation-inference

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CCRss commited on Dec 21, 2023

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@@ -23,7 +23,7 @@ The development process involved training the tokenizer on a large corpus of Kaz
 - Language Specificity: Optimized specifically for the Kazakh language, ensuring high accuracy in tokenization, which is fundamental for NLP tasks.
 - Compatibility with T5 Models: Designed to be compatible with T5-based models, allowing for easy integration into existing T5 frameworks.
 - Versatility: Suitable for a wide range of NLP tasks including but not limited to text summarization, translation, and question-answering in the Kazakh language.
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 ### Usage Scenarios
 This tokenizer is ideal for researchers and developers working on NLP applications targeting the Kazakh language. Whether it's for developing sophisticated language models, translation systems, or other text-based applications, "CCRss/tokenizer_kazakh_t5_new" provides the necessary linguistic foundation for handling Kazakh text effectively.

 - Language Specificity: Optimized specifically for the Kazakh language, ensuring high accuracy in tokenization, which is fundamental for NLP tasks.
 - Compatibility with T5 Models: Designed to be compatible with T5-based models, allowing for easy integration into existing T5 frameworks.
 - Versatility: Suitable for a wide range of NLP tasks including but not limited to text summarization, translation, and question-answering in the Kazakh language.
 ### Usage Scenarios
 This tokenizer is ideal for researchers and developers working on NLP applications targeting the Kazakh language. Whether it's for developing sophisticated language models, translation systems, or other text-based applications, "CCRss/tokenizer_kazakh_t5_new" provides the necessary linguistic foundation for handling Kazakh text effectively.