An outcome-focused guide to what you can do with Howlet Studio, and how easily.
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.
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10 training adapters: From classic machine learning to deep learning and vision; the same experience whatever your framework.
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Experiment tracking: Every run's parameters, metrics and artifacts are recorded automatically; compare runs side by side.
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HPO and AutoML: Four search algorithms and automatic model selection find the best configuration for you.
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Responsible AI: Five fairness metrics, model cards and lineage; model development that is audit-ready.
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GPUs as a governed resource: Quotas, fair scheduling and idle shutdown are built in; cost is tracked per organization.