Giant language fashions (LLMs) like GPT-4, Bloom, and LLaMA have achieved outstanding capabilities by scaling as much as billions of parameters. Nevertheless, deploying these large fashions for inference or fine-tuning is difficult as a result of their immense reminiscence necessities. On this technical weblog, we'll discover methods for estimating and optimizing reminiscence consumption throughout LLM…