Model versions

Just like normal software, machine learning models change and improve over time, and those changes are released as new versions. Whenever a model author retrains a model with new data, fixes a bug in the source code, or updates a dependency, those changes can influence the behavior of the model. The changes are published as new versions, so model authors can make improvements without disrupting the experience for people using older versions of the model. Versioning is essential to making machine learning reproducible: it helps guarantee that a model will behave consistently regardless of when or where it’s being run.

Finding model versions

You can find model versions by going to any model page and clicking on the Versions tab.