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Llama 2 Fine Tuning Sagemaker

Fine-Tuning Llama Models with AWS

Hosting Your Models with AWS

AWS provides various methods for hosting your Llama models. This document outlines the necessary steps to ensure successful hosting.

Fine-Tuning Options

AWS offers two fine-tuning options: instruction fine-tuning and domain adaptation fine-tuning. You can seamlessly switch between these methods by specifying the desired training method.

Instruction Fine-Tuning with Amazon SageMaker

This blog post demonstrates instruction fine-tuning to refine the Llama-2 model for languages beyond English. Follow the steps to create a SageMaker notebook and perform fine-tuning.

Fine-Tuning with AWS Sagemaker Training Jobs

This tutorial guides you through fine-tuning the Llama-2-7b model with Amazon SageMaker Training Jobs. Launch SageMaker Studio and execute the steps outlined in the tutorial to complete the fine-tuning process.

Fine-Tuning with QLoRA

This tutorial provides a comprehensive guide to fine-tuning the LLaMA 2 7-70B model on Amazon SageMaker. It covers the entire process, including setup, QLoRA fine-tuning, and deployment on Amazon SageMaker.


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