How to save xgboost model when use dask?

#1

Here is my code:
cluster = dask.distributed.LocalCluster()

client = dask.distributed.Client(cluster)

dtrain = xgb.dask.DaskDMatrix(client, X_train, y_train)

output = xgb.dask.train(client, {“verbosity”: 2, “tree_method”: “hist”, “objective”:“reg:squarederror”},dtrain,num_boost_round=4,evals=[(dtrain, “train”)],)

How to save my model to local and reload it? It seems like xgb.save() is not work when with dask .

#2 
booster=  output["booster"]
booster.save_model("model.json")