Foundation models are trained on large datasets and require fine-tuning for specific tasks.
A foundation model is typically trained on a large and diverse dataset, serving as a base model for various tasks. Unlike specialized models, it is versatile and requires fine-tuning for different specific tasks to maximize performance.
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