Philipp Schmid • 7/18/2023

Fine-tune LLaMA 2 (7-70B) on Amazon SageMaker

This article provides a step-by-step tutorial for fine-tuning the LLaMA 2 family of large language models (7B, 13B, 70B parameters) on Amazon SageMaker. It explains the use of QLoRA (Quantized Low-Rank Adaptation) for efficient fine-tuning on a single GPU and the Hugging Face PEFT library. The guide covers setting up the environment, preparing datasets, running the fine-tuning process, and deploying the fine-tuned model on SageMaker.

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#Amazon Sagemaker #Peft #Model Fine Tuning