hf-cloud-serving-image-selection

Select serving containers and retrieve image URIs for SageMaker deployments.

10.9k|724|Updated Nov 24, 2025

Search Tags:#deployment #sagemaker #model serving #container selection #image uri

Ready to run

npx skills add https://github.com/huggingface/skills --skill hf-cloud-serving-image-selection

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: hf-cloud-serving-image-selection
Source: https://github.com/huggingface/skills/tree/main/skills/hf-cloud-serving-image-selection
Command: npx skills add https://github.com/huggingface/skills --skill hf-cloud-serving-image-selection

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires aws, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill ensures that the right serving container is chosen for SageMaker model deployment, thereby preventing common issues like stale image failures and incorrect region URIs.

Core Features & Use Cases

Container Selection: Determine the appropriate HuggingFace or generic container for model deployment based on compatibility and performance requirements.
Image URI Retrieval: Obtain the current image URI for deployment from AWS's official Deep Learning Containers catalog.
Use Case: When preparing to deploy a model to a SageMaker endpoint, this Skill can be used to choose the correct container and image URI, avoiding potential deployment failures.

Quick Start

Use the 'hf-cloud-serving-image-selection' skill to get the serving image URI for deploying a text generation model.

Frequently Asked Questions about hf-cloud-serving-image-selection

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I select the right serving container for SageMaker model deployment?▼

To select the right serving container for SageMaker model deployment, you evaluate container compatibility and performance requirements to determine the appropriate HuggingFace or generic container for your model endpoint.

What is the best way to get the current image URI for a SageMaker endpoint?▼

The best way to get the current image URI for a SageMaker endpoint is to retrieve it from AWS's official Deep Learning Containers catalog, ensuring you avoid stale image failures and incorrect region URIs.

Why does my SageMaker model deployment fail with a stale image error?▼

SageMaker model deployment fails with a stale image error when using outdated image URIs, which can be prevented by obtaining the current image URI from the AWS Deep Learning Containers catalog before deployment.

Do I need an AWS account to look up the HuggingFace serving image URI?▼

Yes, you need an AWS environment to look up the HuggingFace serving image URI, as this container selection process requires accessing AWS's Deep Learning Containers catalog for accurate image retrieval.

Can I use HuggingFace containers for text generation model deployment on SageMaker?▼

Yes, you can use HuggingFace containers for text generation model deployment on SageMaker by applying this selection process to obtain the specific serving image URI for your text generation model.