From jeremylongshore-claude-code-plugins-plus-skills
Generates production-ready PyTorch model training code and configurations. Provides step-by-step guidance for data preparation, hyperparameter tuning, and experiment tracking.
How this skill is triggered — by the user, by Claude, or both
Slash command
/jeremylongshore-claude-code-plugins-plus-skills:pytorch-model-trainerThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
This skill provides automated assistance for pytorch model trainer tasks within the ML Training domain.
This skill provides automated assistance for pytorch model trainer tasks within the ML Training domain.
This skill activates automatically when you:
Example: Basic Usage Request: "Help me with pytorch model trainer" 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
npx claudepluginhub jeremylongshore/claude-code-plugins-plus-skillsGuides TensorFlow model training: data prep, hyperparameter tuning, experiment tracking. Auto-activates on 'tensorflow model trainer' mentions.
Organizes PyTorch code into LightningModules, configures Trainers for multi-GPU/TPU, builds data pipelines and callbacks, and runs distributed training (DDP, FSDP, DeepSpeed). Use when structuring training loops or scaling neural-network training.
Provides PyTorch patterns and best practices for building robust, efficient, and reproducible training pipelines, model architectures, and data loading.