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Probabilistic spin logic (PSL) has recently been proposed as a novel computing paradigm that leverages random thermal fluctuations of interacting bodies in a system rather than deterministic switching of binary bits. A PSL circuit is an interconnected network of thermally unstable units called probabilistic bits (p-bits), whose output randomly fluctuates between bits 0 and 1. While the fluctuations generated by p-bits are thermally driven, and therefore, inherently stochastic, the output probability is tunable with an external source. Therefore, information is encoded through probabilities of various configuration of states in the network. Recent studies have shown that these systems can efficiently solve various types of combinatorial optimization problems and Bayesian inference problems that modern computers are unfit for. Previous experimental studies have demonstrated that a single magnetic tunnel junctions (MTJ) designed to be thermally unstable can operate tunable random number generator making it an ideal hardware solution for p-bits. Most proposals for designing an MTJ to operate as a p-bit involve patterning the MTJ as a circular nano-pillar to make the device thermally unstable and then use spin transfer torque (STT) as a tuning mechanism. However, the practical realization of such devices is very challenging since the fluctuation rate of these devices are very sensitive to any device variations or defects caused during fabrication. Despite this challenge, MTJs are still the most promising hardware solution for p-bits because MTJs are very unique in that they can be tuned by multiple other mechanisms such spin orbit torque, magneto-electric coupling, and voltage-controlled exchange coupling. Furthermore, multiple forces can be used simultaneously to drive stochastic switching signals in MTJs. This means there are a large number of methods to tune, or termed as bias, MTJs that can be implemented in p-bit circuits that can alleviate the current challenges of conventional STT driven p-bits. This article serves as a review of all of the different methods that have been proposed to drive random fluctuations in MTJs to operate as a probabilistic bit. Not only will we review the single-biasing mechanisms, but we will also review all the proposed dual-biasing methods, where two independent mechanisms are employed simultaneously. These dual-biasing methods have been shown to have certain advantages such as alleviating the negative effects of device variations and some biasing combinations have a unique capability called ‘two-degrees of tunability’, which increases the information capacity in the signals generated.