Model merging allows for the combination of pre-trained neural network weights into a single model, enhancing performance while reducing training costs. By leveraging existing instruction-following models and focusing solely on specific task datasets, organizations can streamline their processes and achieve remarkable results without the extensive effort typically required for training from scratch.
