August 23, 2024Combinations of Techniques for Reducing Model Size and Computational ComplexityUnlock powerful combinations of model compression techniques like pruning, quantization, and knowledge distillation to supercharge your neural networks. Discover how these synergistic strategies can slash computational demands, boost efficiency, and keep your models blazing fast and ready for real-world deployment!
August 10, 2024Low-Rank Factorization Techniques for Neural Network & LLM OptimizationLow-Rank Factorization is a powerful technique that compresses neural networks by breaking down large weight matrices into simpler, smaller components, reducing computational demands without sacrificing performance. Perfect for optimizing large language models, these methods streamline model size and speed up inference, making them ideal for real-world deployment.