Transformers
Kazakh
text-generation-inference
Inference Endpoints
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@@ -16,7 +16,7 @@ The "CCRss/tokenizer_kazakh_t5_kz" is a specialized tokenizer developed for proc
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  ### Development and Design
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- This tokenizer is built upon the foundations of the T5 model, renowned for its effectiveness in understanding and generating natural language. The T5 model, originally developed by Google Research, is a transformer-based model primarily designed for text-to-text tasks. By leveraging the T5's pre-existing capabilities, the "CCRss/tokenizer_kazakh_t5_new" tokenizer is tailored to handle the unique linguistic characteristics of the Kazakh language.
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  The development process involved training the tokenizer on a large corpus of Kazakh text. This training enables the tokenizer to accurately segment Kazakh text into tokens, a crucial step for any language model to understand and generate language effectively.
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@@ -28,7 +28,7 @@ The development process involved training the tokenizer on a large corpus of Kaz
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  ### Usage Scenarios
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- 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.
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  Link to Google Colab https://colab.research.google.com/drive/1Pk4lvRQqGJDpqiaS1MnZNYEzHwSf3oNE#scrollTo=tTnLF8Cq9lKM
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  ### Acknowledgments
 
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  ### Development and Design
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+ This tokenizer is built upon the foundations of the T5 model, renowned for its effectiveness in understanding and generating natural language. The T5 model, originally developed by Google Research, is a transformer-based model primarily designed for text-to-text tasks. By leveraging the T5's pre-existing capabilities, the "CCRss/tokenizer_kazakh_t5_kz" tokenizer is tailored to handle the unique linguistic characteristics of the Kazakh language.
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  The development process involved training the tokenizer on a large corpus of Kazakh text. This training enables the tokenizer to accurately segment Kazakh text into tokens, a crucial step for any language model to understand and generate language effectively.
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  ### Usage Scenarios
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+ 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_kz" provides the necessary linguistic foundation for handling Kazakh text effectively.
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  Link to Google Colab https://colab.research.google.com/drive/1Pk4lvRQqGJDpqiaS1MnZNYEzHwSf3oNE#scrollTo=tTnLF8Cq9lKM
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  ### Acknowledgments