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Deploy Model Anywhere on AWS

Project description

Easy Model Deployer - Simple, Efficient, and Easy-to-Integrate


Latest News 🔥

  • [2025/03] We officially released EMD!

About

EMD (Easy Model Deployer) is a lightweight tool designed to simplify model deployment. Built for developers who need reliable and scalable model serving without complex setup.

Key Features

  • One-click deployment of models to the cloud (Amazon SageMaker, Amazon ECS, Amazon EC2)
  • Diverse model types (LLMs, VLMs, Embeddings, Vision, etc.)
  • Rich inference engine (vLLM, TGI, Lmdeploy, etc.)
  • Different instance types (CPU/GPU/AWS Inferentia)
  • Convenient integration (OpenAI Compatible API, LangChain client, etc.)

Notes

  • OpenAI Compatible API is supported only for Amazon ECS and Amazon EC2 deployment.

Table of Contents

Architecture

Deploy models to the cloud with EMD will use the following components in Amazon Web Services:

alt text

Getting Started

Installation

Install EMD with pip, currently only support for Python 3.9 and above:

pip install https://github.com/aws-samples/easy-model-deployer/releases/download/main/emd-0.6.0-py3-none-any.whl

Visit our documentation to learn more.

Usage

Choose your default aws profile.

emd config set-default-profile-name

Notes: If you don't set aws profile, it will use the default profile in your env (suitable for Temporary Credentials). Whenever you want to switch deployment accounts, run emd config set-default-profile-name alt text

Bootstrap emd stack

emd bootstrap

Notes: This is going to set up the necessary resources for model deployment. Whenever you change EMD version, run this command again. alt text

Quickly see what models are supported by emd list-supported-models. This command will output all information related to deployment. The following command is recommended to just check the model type. (Plese check Supported Models for complete information.)

emd list-supported-models | jq -r '.[] | "\(.model_id)\t\(.model_type)"' | column -t -s $'\t' | sort

Choose deployment parameters interactively by emd deploy or deploy with one command

emd deploy --model-id DeepSeek-R1-Distill-Qwen-1.5B --instance-type g5.8xlarge --engine-type vllm --framework-type fastapi --service-type sagemaker --extra-params {} --skip-confirm

Notes: Get complete parameters by emd deploy --help and find the values of the required parameters here When you see "Waiting for model: ...", it means the deployment task has started, you can quit the current task by ctrl+c. alt text

Check deployment status.

emd status

alt text Notes: EMD allows to launch multiple deployment tasks at the same time.

Quick functional verfication or check our documentation for integration examples.

emd invoke DeepSeek-R1-Distill-Qwen-1.5B

Notes: Find ModelId in the output of emd status. alt text

Delete the deployed model

emd destroy DeepSeek-R1-Distill-Qwen-1.5B

Notes: Find ModelId in the output of emd status. alt text

Documentation

For advanced configurations and detailed guides, visit our documentation site.

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

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