Pre-caching at edge nodes may improve resource efficiency for future content-centric cellular networks by bringing contents closer to users. However, which mode (muticast or unicast) should be selected for the efficient delivery of those cached contents is still not well addressed, especially at the situation that some key parameters such as content popularity and transmission environments are unknown. To solve this problem, the criterion of delivery mode selection is studied based on the learning policy of multi-armed bandit(MAB). According to the criterion, a mode selection algorithm is proposed. In this algorithm, edge nodes can choose the better delivery modes in the current slot only dependent on existing observations in the previous slot. Performance evaluation results validate our analyses and proposals on the mode selection.