Remove unnecessary comment

Author: aliazzzdat

template/{{.input_root_dir}}/{{template `project_name_alphanumeric_underscore` .}}/validation/notebooks/ModelValidation.py.tmpl

@@ -312,26 +312,19 @@ data = rounded_taxi_data(data)
 # COMMAND ----------
 
 {{ if (eq .input_include_feature_store `yes`) }}
-###########################################################################################
-# Temporary fix as FS model can't predict as pyfunc model                                 #
-# MLflow evaluate can take a lambda function instead of model uri for model               #
-# but not for baseline model it requires model_uri (baseline comparison set to false)     #
-###########################################################################################
+# Temporary fix as FS model can't predict as a pyfunc model
+# MLflow evaluate can take a lambda function instead of a model uri for a model
+# but id does not work for the baseline model as it requires a model_uri (baseline comparison is set to false)
 
 from databricks.feature_store import FeatureStoreClient
 
-
 def get_fs_model(df):
     fs_client = FeatureStoreClient()
     return (
         fs_client.score_batch(model_uri, spark.createDataFrame(df))
         .select("prediction")
         .toPandas()
     )
-
-
-###########################################################################################
-
 {{ end }}
 
 training_run = get_training_run(model_name, model_version)