Is it compatible with standard MLOps workflows?

Absolutely, it is designed to automate the manual overhead of tracking model iterations, fitting seamlessly into modern MLOps practices.

Does it support performance metric comparisons?

Yes, you can ask Claude to retrieve and display performance metrics for specific versions to compare results and identify regressions.

How does Claude track model versions?

Claude interacts with the model-versioning-tracker plugin to log metadata, performance metrics, and version identifiers in a structured registry within your project.

What tools does this skill require?

It utilizes standard file system and bash tools like Read, Write, and Grep to manage versioning data within your environment.

Can I use this for deep learning models?

Yes, this skill is designed for any AI/ML model type, including deep learning, where versioning and performance monitoring are required.

AI Model Versioning Tracker

Name: AI Model Versioning Tracker
Author: BbgnsurfTech

byBbgnsurfTech

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데이터 과학 및 ML

Manages and tracks AI/ML model versions, lineage, and performance metrics directly within your development environment.

소개

The Model Versioning Tracker skill empowers Claude to act as a specialized registry manager for AI/ML projects. It automates the logging of new model iterations, tracks lineage to maintain data provenance, and retrieves critical performance metrics. By integrating version control into the model development lifecycle, it ensures that developers can easily compare different model versions, monitor performance regressions, and maintain a clear history of model evolution without leaving the terminal.

주요 기능

Performance metric retrieval and historical comparison
3 GitHub stars
Automated model version logging and registry management
Integration with AI/ML development workflows
Lineage tracking for data and model provenance
Robust error handling for version control operations

사용 사례

Tracking iterations of an image classification or NLP model
Maintaining a historical record of model changes and metadata
Auditing model performance metrics across multiple production versions

소개

주요 기능

Performance metric retrieval and historical comparison
3 GitHub stars
Automated model version logging and registry management
Integration with AI/ML development workflows
Lineage tracking for data and model provenance
Robust error handling for version control operations

사용 사례

Tracking iterations of an image classification or NLP model
Maintaining a historical record of model changes and metadata
Auditing model performance metrics across multiple production versions