Esmail Atta Gumaan
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license: mit
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license: mit
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datasets:
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- opus_books
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LlTRA stands for: Language to Language Transformer model from the paper "Attention is all you Need", building transformer model:Transformer model from scratch and using it for translation using pytorch.
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Problem Statement:
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In the rapidly evolving landscape of natural language processing (NLP) and machine translation, there exists a persistent challenge in achieving accurate and contextually rich language-to-language transformations. Existing models often struggle with capturing nuanced semantic meanings, context preservation, and maintaining grammatical coherence across different languages. Additionally, the demand for efficient cross-lingual communication and content generation has underscored the need for a versatile language transformer model that can seamlessly navigate the intricacies of diverse linguistic structures.
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Goal:
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Develop a specialized language-to-language transformer model that accurately translates from the Arabic language to the English language, ensuring semantic fidelity, contextual awareness, cross-lingual adaptability, and the retention of grammar and style. The model should provide efficient training and inference processes to make it practical and accessible for a wide range of applications, ultimately contributing to the advancement of Arabic-to-English language translation capabilities.
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