An artifact is a discrete object produced, stored, or consumed within a machine learning or software workflow. Examples include datasets, model files, training logs, configuration files, evaluation reports, containers, and other versioned assets needed to build or operate a system.
An artifact is a discrete entity or piece of data produced and consumed by a machine learning workflow. Examples of artifacts include datasets, models, input files, and training logs.