Propose an alternative approach using Greedy algorithms to improve the efficiency of your model’s training process. Explain the tradeoffs involved in this approach.

Break down the NLP task into simpler components (e.g., language modeling, entity recognition) and train smaller models on these tasks first. Then, combine the trained components to form the final complex model. This approach reduces computational costs and speeds up training time by handling each component in isolation, but may not guarantee an optimal complete solution.