1  from sklearn.datasets import load_iris
 2  from sklearn.linear_model import LogisticRegression
 3  
 4  import mlflow
 5  from mlflow.models import infer_signature
 6  
 7  X, y = load_iris(return_X_y=True, as_frame=True)
 8  model = LogisticRegression().fit(X, y)
 9  signature = infer_signature(X, model.predict(X))
10  
11  with mlflow.start_run() as run:
12      mlflow.sklearn.log_model(model, name="model", signature=signature)
13      runs_uri = f"runs:/{run.info.run_id}/model"
14      model = mlflow.sklearn.load_model(runs_uri)
15      print(model.predict(X)[:10])