GitHub - aws-samples/sample-aws-deep-learning-containers (original) (raw)

AWS Deep Learning Containers Samples

This repository contains sample code and configurations for using AWS Deep Learning Containers (DLCs) in various scenarios. AWS Deep Learning Containers are Docker images pre-installed with deep learning frameworks and tools, optimized for performance on AWS infrastructure.

Repository Structure

• vllm-samples/: Samples for deploying vLLM (a high-throughput serving engine for LLMs) using AWS Deep Learning Containers
  • deepseek/: Samples for deploying DeepSeek models
    * eks/: Configuration files and instructions for deploying DeepSeek models on Amazon EKS with GPU support, EFA, and FSx Lustre integration
• mlflow/: Samples for using SageMaker managed MLflow with Deep Learning Containers and Deep Learning AMIs
  • dlc-with-mlflow/: Sample for integrating AWS DLCs with SageMaker managed MLflow for training. See README for detailed instructions.

AWS Deep Learning Containers

AWS Deep Learning Containers provide optimized environments with pre-installed deep learning frameworks and tools:

• Performance Optimized: Tuned for maximum performance on AWS infrastructure
• Pre-configured: Ready-to-use environments with popular frameworks
• Regularly Updated: Latest versions of frameworks and security patches
• AWS Integration: Seamless integration with AWS services like EKS, ECS, and SageMaker

Learn more about AWS Deep Learning Containers.