Training & Experiments
Model training in Howlet is a team sport: experiments are recorded automatically, hyperparameter searches run in parallel, fairness metrics are reported and idle GPUs shut themselves down.
- 10 training adapters: From classic machine learning to deep learning and vision; the same experience whatever your framework.
- Experiment tracking: Every run's parameters, metrics and artifacts are recorded automatically; compare runs side by side.
- HPO and AutoML: Four search algorithms and automatic model selection find the best configuration for you.
- Responsible AI: Five fairness metrics, model cards and lineage; model development that is audit-ready.
- GPUs as a governed resource: Quotas, fair scheduling and idle shutdown are built in; cost is tracked per organization.