Skip to main content

Training models directly on your datastore

Model instances may be trained if a trainer is set on the Model when db.apply is called. When models are trained, if CFG.cluster.compute has been configured with a ray scheduler, then superduperdb deploys a job on the connected ray cluster.

Basic pattern​

from superduperdb.ext.<framework> import <Framework>Trainer
from superduperdb.ext.<framework> import <ModelCls>

db.apply(
<ModelCls>(
*args,
trainer=<Framework>Trainer(**trainer_kwargs),
**kwargs,
)
)

Fitting/ training models by framework​

Not all Model types are trainable. We support training for the following frameworks:

FrameworkTraining Link
Scikit-Learnlink
PyTorchlink
Transformerslink