Deploying large language models (LLMs) effectively to address real-world challenges requires careful consideration of scaling strategies. While increasing model size and training data can often lead to performance improvements, it's crucial to also optimize model architectures for specific tasks and domains. Furthermore, exploiting the power of dis

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