AWS Inferentia and AWS Trainium are two new AWS services that make it easier and more cost-effective to deploy machine learning (ML) models on Amazon SageMaker JumpStart. AWS Inferentia is a high-performance ML inference chip that delivers up to 3x the performance of previous-generation chips at a 40% lower cost. AWS Trainium is a fully managed ML training service that makes it easy to train large ML models on AWS.
Together, AWS Inferentia and AWS Trainium provide a comprehensive solution for deploying ML models on Amazon SageMaker JumpStart. AWS Inferentia can be used to accelerate model inference, while AWS Trainium can be used to train new models or retrain existing models on the latest data. This combination of services provides the flexibility, scalability, and cost-effectiveness that businesses need to deploy and operate ML models.
Benefits of Using AWS Inferentia and AWS Trainium
There are several benefits to using AWS Inferentia and AWS Trainium for deploying ML models on Amazon SageMaker JumpStart. These benefits include:
- Cost-effectiveness: AWS Inferentia and AWS Trainium are designed to be cost-effective, making it easier for businesses to deploy and operate ML models.
- Performance: AWS Inferentia is a high-performance ML inference chip that delivers up to 3x the performance of previous-generation chips at a 40% lower cost.
- Ease of use: AWS Trainium is a fully managed ML training service that makes it easy to train large ML models on AWS.
- Flexibility: AWS Inferentia and AWS Trainium can be used to deploy and operate a wide range of ML models, including Llama 3 models.
How to Deploy a Llama 3 Model on Amazon SageMaker JumpStart Using AWS Inferentia and AWS Trainium
Deploying a Llama 3 model on Amazon SageMaker JumpStart using AWS Inferentia and AWS Trainium is a simple and straightforward process. The following steps provide a general overview of the process:
- Create an AWS Inferentia instance. The first step is to create an AWS Inferentia instance. This can be done through the AWS Management Console or the AWS CLI.
- Train a Llama 3 model using AWS Trainium. The next step is to train a Llama 3 model using AWS Trainium. This can be done through the AWS Management Console or the AWS CLI.
- Deploy the Llama 3 model on Amazon SageMaker JumpStart. The final step is to deploy the Llama 3 model on Amazon SageMaker JumpStart. This can be done through the AWS Management Console or the AWS CLI.
Conclusion
AWS Inferentia and AWS Trainium are two new AWS services that make it easier and more cost-effective to deploy ML models on Amazon SageMaker JumpStart. By using AWS Inferentia and AWS Trainium together, businesses can take advantage of the cost-effectiveness, performance, ease of use, and flexibility of these services to deploy and operate a wide range of ML models.
Kind regards J.O. Schneppat.
