npx claudepluginhub kanpuriyanawab/autotune# /train — Legacy Training Shortcut This is a lightweight shortcut for experienced users. Prefer `/plan-experiments` and `/run-experiment` for the full workflow. ## Steps 1. Call `check_gpu`. 2. Parse model, dataset, and hyperparameters. 3. Call `run_training`. 4. Report the run directory and training metrics.
/trainTrains an ML model on specified dataset and parameters using scikit-learn, PyTorch, TensorFlow, or XGBoost. Generates code for data prep, training with CV, metrics, and model saving.
/trainTrains a text classifier model with labeled examples using required category label and text or file pattern.
/trainTrains machine learning or deep learning models in the project via standard workflow: environment checks, data preparation, configuration, launch with GPU support, and monitoring.
This is a lightweight shortcut for experienced users. Prefer /plan-experiments
and /run-experiment for the full workflow.
check_gpu.run_training.