The new pre-trained model exploration page showcases more than twenty pre-trained models that can be deployed and immediately used in your Baseten applications or called via API requests.
Find a model that works for your use case by filtering by tags and libraries. And if there is an open-source model that you’d like to see us add to our pre-trained model library, let us know at email@example.com.
When you add a model block to a worklet, you can now select which version of the model is invoked. By default, the primary version of the model will be selected.
This is especially useful for keeping production behavior consistent as you deploy new model versions until you have a chance to update the applications that depend on these models.
A handful of small-but-mighty changes to make Baseten more joyful to use:
Added documentation around specific versions of model frameworks that are officially supported by the Baseten Python client
Fixed issue with AWS SageMaker input format selector when deploying a model from SageMaker
Performance fixes and bug improvements