From jeremylongshore-claude-code-plugins-plus-skills
Assists with model export helper operations in ML deployment, offering step-by-step guidance, production-ready code, configurations, and best practices for serving, MLOps pipelines, monitoring, and optimization.
npx claudepluginhub jeremylongshore/claude-code-plugins-plus-skills --plugin langchain-py-packThis skill is limited to using the following tools:
This skill provides automated assistance for model export helper tasks within the ML Deployment domain.
Provides step-by-step guidance, code, and configurations for TorchScript exporter tasks in ML deployment, covering model serving, MLOps pipelines, monitoring, and production optimization.
Deploys trained ML models to production via REST APIs, Docker containers, Kubernetes clusters, with data validation, error handling, and performance monitoring.
Builds production ML systems with PyTorch 2.x, TensorFlow, and modern frameworks for model serving, feature engineering, A/B testing, monitoring, and infrastructure.
Share bugs, ideas, or general feedback.
This skill provides automated assistance for model export helper tasks within the ML Deployment domain.
This skill activates automatically when you:
Example: Basic Usage Request: "Help me with model export helper" Result: Provides step-by-step guidance and generates appropriate configurations
| Error | Cause | Solution |
|---|---|---|
| Configuration invalid | Missing required fields | Check documentation for required parameters |
| Tool not found | Dependency not installed | Install required tools per prerequisites |
| Permission denied | Insufficient access | Verify credentials and permissions |
Part of the ML Deployment skill category. Tags: mlops, serving, inference, monitoring, production