Redefining Efficiency: Beyond Compute-Optimal Training to Predict Language Model Performance on Downstream Tasks

In artificial intelligence, scaling laws serve as useful guides for developing Large Language Models (LLMs). Like skilled directors, these laws coordinate models’ growth, revealing development patterns that go beyond mere computation. With each step forward, these models become more sophisticated, unlocking the intricacies of human expression with careful accuracy. Besides, scaling laws provide limitless potential […]

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