Thanks for your reply LRALVA, When i tried to run mlflow.spark.log_model(pipeline_model, "spark_pipeline_model") on my already saved model which was saved using random forest a long back. log_model gives me error that model is not a spark flavor. So i tried with mlflow.sklearn.log_model(pipeline_model, "spark_pipeline_model") which worked and I am able to register model under models but when I load it back and run transform function on it it is giving me error

AttributeError: 'str' object has no attribute 'transform'

Code I am running to load -

import mlflow
import mlflow.spark
from mlflow.tracking import MlflowClient

# Load the model in Unity Catalog cluster:
model_uri = "models:/sparkML_rf2022_2_0/latest" # or specific version
loaded_model = mlflow.sklearn.load_model(model_uri)
df = spark.read.parquet('<data/path>')
# Use the model for predictions
predictions = loaded_model.transform(df)