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packaging-model-for-deployment

Community

Ship models with schemas and smoke tests.

Data & Analytics#fastapi#machine learning#manifest#schema validation#model deployment#smoke test#joblib
Authorrocklambros
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill turns a trained notebook model into a deployable, self-describing artifact so teams can ship it without rebuilding preprocessing, guessing inputs, or discovering serving bugs late.

Core Features & Use Cases

  • Single fitted pipeline: Packages preprocessing and the model together to prevent training-serving skew.
  • Versioned deployment bundle: Produces a manifest, input schema, output schema, and saved artifact that can be reviewed and tracked.
  • Smoke-test gate: Requires disk-based golden tests so CI can verify the saved artifact before promotion.
  • Use cases: FastAPI inference endpoints, batch scoring jobs, cross-runtime serving with ONNX or TorchScript, and handoff to platform or SRE teams.

Quick Start

Ask the assistant to package my trained model for deployment and include a versioned artifact, input and output schemas, a manifest, and a smoke test that runs from disk.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: packaging-model-for-deployment
Download link: https://github.com/rocklambros/rcs/archive/main.zip#packaging-model-for-deployment

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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