Artificial Intelligence
Best prompting practices for using Meta Llama 3 with Amazon SageMaker JumpStart
In this post, we dive into the best practices and techniques for prompting Meta Llama 3 using Amazon SageMaker JumpStart to generate high-quality, relevant outputs. We discuss how to use system prompts and few-shot examples, and how to optimize inference parameters, so you can get the most out of Meta Llama 3.
Use Llama 3.1 405B for synthetic data generation and distillation to fine-tune smaller models
Today, we are excited to announce the availability of the Llama 3.1 405B model on Amazon SageMaker JumpStart, and Amazon Bedrock in preview. The Llama 3.1 models are a collection of state-of-the-art pre-trained and instruct fine-tuned generative artificial intelligence (AI) models in 8B, 70B, and 405B sizes. Amazon SageMaker JumpStart is a machine learning (ML) hub that provides access to algorithms, models, and ML solutions so you can quickly get started with ML. Amazon Bedrock offers a straightforward way to build and scale generative AI applications with Meta Llama models, using a single API.

