model = client.create_model(
  name="<model_name>",
  ontology_id="<ontology_id>"
)

model = client.get_model("<model_id>")

# from labelbox import Model
models = client.get_models(where=(Model.name == "<model_name>"))

model.create_model_run(name="<model_run_name>"

# optionally, you can supply details of the model run config
model.create_model_run(
  name="<model_run_with_config>",
  config={
    "learning_rate": 0.001,
    "batch_size": 32
  }
)

model.delete()

# name (str)
model.name

# get the model runs (relationship to ModelRun objects)
model_runs = model.model_runs()

# inspect one model run
next(model_runs)

# inspect all model runs
for model_run in model_runs:
  print(model_run)