Llama 2 models are available today in Amazon SageMaker Studio in us-east 1, us-west 2, eu-west-1, and ap-southeast-1 Regions. The model is deployed in an AWS secure environment and under your VPC controls, helping ensure data security. You can now discover and deploy Llama 2 with a few clicks in Amazon SageMaker Studio or programmatically through the SageMaker Python SDK, enabling you to derive model performance and MLOps controls with SageMaker features such as Amazon SageMaker Pipelines, Amazon SageMaker Debugger, or container logs. ML practitioners can deploy foundation models to dedicated Amazon SageMaker instances from a network isolated environment and customize models using SageMaker for model training and deployment. With SageMaker JumpStart, ML practitioners can choose from a broad selection of publicly available foundation models. Regardless of which version of the model a developer uses, the responsible use guide from Meta can assist in guiding additional fine-tuning that may be necessary to customize and optimize the models with appropriate safety mitigations. The tuned models are intended for assistant-like chat, whereas pre-trained models can be adapted for a variety of natural language generation tasks. Llama 2 was pre-trained on 2 trillion tokens of data from publicly available sources. According to Meta, the tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align to human preferences for helpfulness and safety. It comes in a range of parameter sizes-7 billion, 13 billion, and 70 billion-as well as pre-trained and fine-tuned variations. Llama 2 is intended for commercial and research use in English. Llama 2 is an auto-regressive language model that uses an optimized transformer architecture. In this post, we walk through how to use Llama 2 models via SageMaker JumpStart. You can easily try out these models and use them with SageMaker JumpStart, which is a machine learning (ML) hub that provides access to algorithms, models, and ML solutions so you can quickly get started with ML. Fine-tuned LLMs, called Llama-2-chat, are optimized for dialogue use cases. The Llama 2 family of large language models (LLMs) is a collection of pre-trained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. Today, we are excited to announce that Llama 2 foundation models developed by Meta are available for customers through Amazon SageMaker JumpStart.
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