52 lines
2.8 KiB
Markdown
52 lines
2.8 KiB
Markdown
---
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name: tracking-model-versions
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description: |
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This skill enables Claude to track and manage AI/ML model versions using the model-versioning-tracker plugin. It should be used when the user asks to manage model versions, track model lineage, log model performance, or implement version control for AI/ML models. Use this skill when the user mentions "track versions", "model registry", "MLflow", or requests assistance with AI/ML model deployment and management. This skill facilitates the implementation of best practices for model versioning, automation of model workflows, and performance optimization.
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allowed-tools: Read, Write, Edit, Grep, Glob, Bash
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version: 1.0.0
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---
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## Overview
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This skill empowers Claude to interact with the model-versioning-tracker plugin, providing a streamlined approach to managing and tracking AI/ML model versions. It ensures that model development and deployment are conducted with proper version control, logging, and performance monitoring.
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## How It Works
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1. **Analyze Request**: Claude analyzes the user's request to determine the specific model versioning task.
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2. **Generate Code**: Claude generates the necessary code to interact with the model-versioning-tracker plugin.
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3. **Execute Task**: The plugin executes the code, performing the requested model versioning operation, such as tracking a new version or retrieving performance metrics.
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## When to Use This Skill
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This skill activates when you need to:
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- Track new versions of AI/ML models.
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- Retrieve performance metrics for specific model versions.
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- Implement automated workflows for model versioning.
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## Examples
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### Example 1: Tracking a New Model Version
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User request: "Track a new version of my image classification model."
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The skill will:
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1. Generate code to log the new model version and its associated metadata using the model-versioning-tracker plugin.
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2. Execute the code, creating a new entry in the model registry.
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### Example 2: Retrieving Performance Metrics
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User request: "Get the performance metrics for version 3 of my sentiment analysis model."
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The skill will:
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1. Generate code to query the model-versioning-tracker plugin for the performance metrics associated with the specified model version.
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2. Execute the code and return the metrics to the user.
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## Best Practices
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- **Data Validation**: Ensure input data is validated before logging model versions.
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- **Error Handling**: Implement robust error handling to manage unexpected issues during version tracking.
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- **Performance Monitoring**: Continuously monitor model performance to identify opportunities for optimization.
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## Integration
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This skill integrates with other Claude Code plugins by providing a centralized location for managing AI/ML model versions. It can be used in conjunction with plugins that handle data processing, model training, and deployment to ensure a seamless AI/ML workflow. |