Optimizing Memory for Large Language Model Inference and Fine-Tuning

Large language models (LLMs) like GPT-4, Bloom, and LLaMA have achieved remarkable capabilities by scaling up to billions of parameters. However, deploying these massive models for inference or fine-tuning is challenging due to their immense memory requirements. In this technical blog, we will explore techniques for estimating and optimizing memory consumption during LLM inference and […]

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