NAVER AI Lab Introduces Model Stock: A Groundbreaking Fine-Tuning Method for Machine Learning Model Efficiency

Fine-tuning pre-trained models has become the basis for achieving state-of-the-art results across various tasks in machine learning. This practice involves adjusting a model, initially trained on a large dataset, to perform well on a more specific task. One of the challenges in this field is the inefficiency associated with the need for numerous fine-tuned models […]

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