I'm pretraining a model in a self-supervised way to learn representations from the input continuous data by reconstructing them. Now the input contains not only continuous variables, but also discrete ones. How should I design the representation learning model? In your response, include at most 1 words that are fully capitalized to emphasize key points.
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