This paper presents a 2-SPRT based multiple-model hypothesis testing approach for cooperative spectrum sensing to detecting unknown signal that may have multiple possible distributions with different structural or parametric uncertainties. The traditional sequential probability ratio test (SPRT) based cooperative sensing scheme is promising, because it is optimal for specified simple hypotheses. However, it may suffer from SPRT's lack of an upper bound on its stopping time, especially in the mis-specified case; moreover, it cannot directly handle the sequential cooperative sensing with modeling uncertainties that may have multiple possible distributions. The proposed 2-SPRT based scheme not only cope with the above problems, but also is in a setting that can provide efficient detection results. Performance of the proposed scheme is evaluated for spectrum sensing in an illustrative scenario. Simulation results demonstrate its detection efficiency compared with the traditional schemes.