Mastering LLM Techniques: Inference Optimization – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-03-13T20:13:39Z http://www.open-lab.net/blog/feed/ Shashank Verma <![CDATA[Mastering LLM Techniques: Inference Optimization]]> http://www.open-lab.net/blog/?p=73739 2024-01-25T18:57:32Z 2023-11-17T15:00:00Z Stacking transformer layers to create large models results in better accuracies, few-shot learning capabilities, and even near-human emergent abilities on a...]]> Stacking transformer layers to create large models results in better accuracies, few-shot learning capabilities, and even near-human emergent abilities on a...

Stacking transformer layers to create large models results in better accuracies, few-shot learning capabilities, and even near-human emergent abilities on a wide range of language tasks. These foundation models are expensive to train, and they can be memory- and compute-intensive during inference (a recurring cost). The most popular large language models (LLMs) today can reach tens to hundreds of��

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