How Mamba-Shedder compression optimizes language models

While large, pre-trained models have achieved outstanding results in general language sequence modeling, an alternative architecture called Selective Structured State Space Models has arrived to address inefficiencies in Transformers. In this article, you’ll learn how the novel Mamba-Shedder compression method demonstrates that redundant components can be removed with only a minor impact on model performance. A few other highlights: 👍 Efficient pruning techniques 👍 Accelerated inference 👍 Recovery tuning Read more here: https://intel.ly/3U9jraZ #ArtificialIntelligence #DeepLearning #Developer