Is it possible to pass a pydantic model as parameter to

run_deployment

? I have a setup similar to the following, but when I pass the pydantic model I get some weird behavior.

class Config(BaseModel):
   ...

@flow(name="subflow")
def subflow(config: Config = Config()):
    do_something()

@flow
def main_flow(config: Config = Config()):
    run_deployment(name="subflow", parameters={"config": config})

It takes in a dictionary but you can convert pydantic model with

model.dict()

.

The subflow expects a pydantic model instead of a dict though, is that a problem?