SeedLM: A Post-Training Compression Method that Uses Pseudo-Random Generators to Efficiently Encode and Compress LLM Weights Asif Razzaq Artificial Intelligence Category – MarkTechPost
[[{“value”:” The ever-increasing size of Large Language Models (LLMs) presents a significant challenge for practical deployment. Despite their transformative impact on natural language processing, these models are often hindered by high memory transfer requirements, which pose a bottleneck during autoregressive generation. This results in high… Read More »SeedLM: A Post-Training Compression Method that Uses Pseudo-Random Generators to Efficiently Encode and Compress LLM Weights Asif Razzaq Artificial Intelligence Category – MarkTechPost