Amazon SageMaker · Deployment

Chooses the right serving container and current image URI for deploying a Hugging Face model to a SageMaker endpoint, preferring Hugging Face images over generic ones.

huggingface/skills

Sets up an isolated Python environment with a supported interpreter and current boto3 before any SageMaker deployment, training or AWS automation code runs.

huggingface/skills

Deploys SageMaker endpoints with autoscaling, CloudWatch alarms and tags on by default, using scripts for real-time, scale-to-zero and async setups.

huggingface/skills

Entry point for hosting a model on Amazon SageMaker: asks a few questions, picks a deployment pathway and hands off to the specialist skills.

huggingface/skills

Implement a production SageMaker endpoint with autoscaling, CloudWatch alarms, and tags.

waybarrios/opencode-power-pack

Select and verify the current region-specific serving container URI for a SageMaker model deployment.

waybarrios/opencode-power-pack

Generates code that deploys fine-tuned models from SageMaker Serverless Model Customization to SageMaker endpoints or Bedrock.

awslabs/agent-plugins

Plan and coordinate a model deployment to Amazon SageMaker, including serving stack and real-time versus async inference.

waybarrios/opencode-power-pack

Selects, deploys, and customizes AI models on Amazon SageMaker.

aws/agent-toolkit-for-aws

Deploy sagemaker endpoint deployer operations. An agent skill from jeremylongshore/tons-of-skills-marketplace.

jeremylongshore/tons-of-skills-marketplace