Pytorch Deployment
Automates PyTorch model deployment to cloud environments, streamlining inference serving and scaling workflows.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add pytorch-deployment npx -- -y @trustedskills/pytorch-deployment
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"pytorch-deployment": {
"command": "npx",
"args": [
"-y",
"@trustedskills/pytorch-deployment"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill automates the deployment of PyTorch models. It handles tasks such as containerizing a model, pushing images to registries, and deploying them on various platforms. The goal is to streamline the process of making PyTorch models accessible for inference or other applications.
When to use it
- You've trained a PyTorch model and need to make it available for real-time predictions.
- You want to automate the process of updating your deployed PyTorch models with new versions.
- You are building a scalable machine learning pipeline that requires consistent deployment practices.
- You need to deploy PyTorch models across different environments (e.g., cloud, edge devices).
Key capabilities
- Containerization of PyTorch models
- Image registry pushing
- Deployment on various platforms
Example prompts
- "Deploy my PyTorch model located in
/app/model.pthto Docker Hub with the taglatest." - "Create a container image for my PyTorch inference server and push it to AWS ECR."
- “Update the deployed version of my PyTorch model.”
Tips & gotchas
The skill requires familiarity with Docker and cloud deployment platforms. Ensure your PyTorch environment is properly configured before attempting deployment.
Tags
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
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Passed automated security scans.