Bigger Isn’t Always Better, Balancing Is The Key
Scaling Laws in Machine Learning Scaling laws in machine learning, particularly in large language models (LLMs), describe how model performance improves as you increase resources like model parameters, dataset size (tokens), and compute power. These laws help determine the most efficient way to scale models to maximize performance while minimizing costs. In deep learning, scaling […]
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