As modern IoT systems tend to become increasing larger, complex and intelligent, which makes requirements become higher on the perception and computation capabilities of calculation devices at the edge. The future development of cloud computation focuses on enabling the collaboration of low-power, high-real-time edge computation with low-cost and high-performance. In order to realize the collaboration between edge and cloud to maximize the application value of the advantages of edge and cloud computation, this paper proposed a computing framework for edge model scenario adaptive tasks in edge-cloud system. Firstly, the edge-cloud collaboration mechanism model is constructed based on the difference between inference results of cloud-side model and edge-side model. Secondly, a small amount of edge application-side task samples are employed to incrementally re-train the cloud-side model to the adaption performance of edge-side transferred model from the cloud-side model. Finally, the performance of the edge-size can be maintained by the real-time monitoring of the side-side reasoning results.