Model Deployment
Takes a SageMaker Serverless Model Customization fine-tuned model and generates the code to actually deploy it, either to a SageMaker endpoint or Bedrock. It's methodical about walking through the decision tree: pulls metadata from your training job, figures out whether you've got Nova or an OSS model, shows you eligible targets, then generates pathway-specific deployment code. The workflow is deliberately slow, one confirmation at a time, which feels right given how easy it is to spin up expensive infrastructure by accident. Only handles LoRA fine-tuned models, not full fine-tuning, and it'll check the license terms before deploying. Honest take: this is the boring bridging work between "my model trained" and "I can call my model," automated.
- skills.sh installs
- 154
- GitHub stars
- 938
- last updated
- Jun 11, 2026
Install
$ npx -y skills add awslabs/agent-plugins --skill model-deployment --agent claude-codeInstalls into .claude/skills of the current project.
Files
Model Deployment
Identifies the correct deployment pathway based on model characteristics and generates deployment code.
Scope
This skill supports deploying Nova and OSS models that were fine-tuned through SageMaker Serverless Model Customization only.
Not supported:
- Base models (not fine-tuned)
- Models fine-tuned through other processes
- Full Fine-Tuning (FFT) — only LoRA fine-tuned models are supported
Prerequisites
- The SDK environment has been verified (SDK version, region, execution role). If not done, activate the
sdk-getting-startedskill first.
Principles
- One thing at a time. Each response advances exactly one decision.
- Confirm before proceeding. Wait for the user to agree before moving on. But don't re-ask questions already answered in the conversation — use what you know.
- Don't read files until you need them. Only read pathway references after the pathway is confirmed.
- Use what you know. If conversation history or artifacts already answer a question, confirm your understanding instead of asking again.
Workflow
Step 1: Identify the Training Job
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- Repository
- github.com/awslabs/agent-plugins
- Categories
- Backend & APIs, DevOps & CI/CD, AI & Agent Building, Release Management, Cloud & Infrastructure
- License
- Apache-2.0
- First seen
- Jun 11, 2026
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- Aws Lambda260
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