From jeremylongshore-claude-code-plugins-plus-skills
Generates TorchServe configuration files and operations for ML model serving in production. Provides step-by-step guidance, best practices, code, and validation for MLOps pipelines, inference, and monitoring.
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 torchserve config generator tasks within the ML Deployment domain.
Provides step-by-step guidance and generates configurations for TensorFlow Serving setup in ML deployment, covering model serving, MLOps pipelines, monitoring, and production optimization.
Builds production ML systems with PyTorch 2.x, TensorFlow, and modern frameworks for model serving, feature engineering, A/B testing, monitoring, and infrastructure.
Builds production ML systems with PyTorch 2.x, TensorFlow, Hugging Face, and tools for model serving, feature engineering, A/B testing, and monitoring.
Share bugs, ideas, or general feedback.
This skill provides automated assistance for torchserve config generator tasks within the ML Deployment domain.
This skill activates automatically when you:
Example: Basic Usage Request: "Help me with torchserve config generator" 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