A novel framework named MOHESR suggests a innovative approach to neural machine translation (NMT) by seamlessly integrating dataflow techniques. The framework leverages the power of dataflow architectures for accomplishing improved efficiency and scalability in NMT tasks. MOHESR implements a flexible design, enabling detailed control over the trans