From jeremylongshore-claude-code-plugins-plus-skills
Manages model checkpoints in ML training workflows using PyTorch, TensorFlow, or scikit-learn. Offers guidance, code generation, and best practices for saving/loading models during training, tuning, and tracking.
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 checkpoint manager tasks within the ML Training domain.
Generates PyTorch model trainer code and configs for data preparation, training, hyperparameter tuning, and experiment tracking. Activates on PyTorch training requests.
Executes documented training commands in deep learning research repos for startup verification, short-run checks, full kickoff, or resume, capturing status, checkpoints, and metrics to train_outputs/.
Tracks AI/ML model versions using MLflow: logs hyperparameters/metrics, registers models, manages Staging/Production stages, compares performance, generates model cards.
Share bugs, ideas, or general feedback.
This skill provides automated assistance for model checkpoint manager tasks within the ML Training domain.
This skill activates automatically when you:
Example: Basic Usage Request: "Help me with model checkpoint manager" 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 Training skill category. Tags: ml, training, pytorch, tensorflow, sklearn