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 superduper deploys a job on the connected ray cluster.

Basic pattern

from superduper.ext.<framework> import <Framework>Trainer
from superduper.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:

Framework	Training Link
Scikit-Learn	link
PyTorch	link
Transformers	link