Enable live reload with draft models

Slow dev loops break flow state and make for a frustrating experience. And for data scientists, slow dev loops make all but the most essential deployment workflows too expensive and time consuming to even consider.

To speed up dev loops in model deployment, Baseten is introducing draft models. For more, read our blog post on using this feature to accelerate your workflows.

By default, the baseten.deploy() command deploys your model as a draft. Here’s a simple example:

import baseten

baseten.deploy(
    packaged_model,
    model_name="Penguin Predictor"
)

When you're ready to publish your model, just pass publish=True to the same deploy command.

To get started with draft models, read the docs or try our demo notebook!