
Meta's Llama 2 foundation models are now available in Amazon SageMaker JumpStart, enabling customers to easily discover, deploy, and fine-tune these large language models ranging from 7B to 70B parameters for text generation and dialogue applications.


<div><p>This article announces the availability of Meta's Llama 2 foundation models through Amazon SageMaker JumpStart for fine-tuning and deployment.</p><ul><li>Llama 2 models range from 7B to 70B parameters with pre-trained and chat-optimized variants</li><li>Deploy models via SageMaker Studio UI or Python SDK with a few clicks</li><li>Fine-tune Llama 2 7B and 13B models on your own datasets in 1-2 hours</li><li>Chat models accept conversation history; pre-trained models perform text completion</li><li>Available in five AWS regions with inference and fine-tuning capabilities</li><li>Supports inference parameters like max_new_tokens, temperature, and top_p</li><li>Uses FSDP and LoRA methods for efficient fine-tuning</li></ul><p>Llama 2 models are now accessible through SageMaker JumpStart, enabling developers to quickly deploy and customize large language models for various NLP tasks without extensive infrastructure setup.</p></div>


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