From jeremylongshore-claude-code-plugins-plus-skills
Assists with model pruning helper operations in ML deployment. Provides step-by-step guidance, generates code and configurations for model serving, MLOps pipelines, monitoring, and production 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 pruning helper tasks within the ML Deployment domain.
Optimizes ML models for reduced size, faster inference, and edge deployment using quantization, pruning, knowledge distillation, ONNX export, and TensorRT.
Optimizes ML inference latency via model compression, distillation, pruning, quantization, caching strategies, and edge deployment patterns.
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.
Share bugs, ideas, or general feedback.
This skill provides automated assistance for model pruning helper tasks within the ML Deployment domain.
This skill activates automatically when you:
Example: Basic Usage Request: "Help me with model pruning 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