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## Model Description
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It was developed as a lightweight experimental model to explore **Turkish-specific tokenization and morphology-aware pretraining** using the custom [turkish_tokenizer](https://github.com/malibayram/turkish-tokenizer).
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The model follows the **LLaMA-style causal transformer** architecture and was trained with a context length of 256 tokens over ~372M tokens in total.
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## Model Description
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`llama_50m_tr_tokenizer_news` is a **50 million parameter Turkish language model** trained from scratch on the `habanoz/news-tr-1.8M` dataset.
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It was developed as a lightweight experimental model to explore **Turkish-specific tokenization and morphology-aware pretraining** using the custom [turkish_tokenizer](https://github.com/malibayram/turkish-tokenizer).
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The model follows the **LLaMA-style causal transformer** architecture and was trained with a context length of 256 tokens over ~372M tokens in total.
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