def train_model_locally(train:snowflake.snowpark.table.Table):
    from sklearn.tree import DecisionTreeClassifier

    #convert into pd dataframes

    train = train.to_pandas()

    xtrain,ytrain = train.drop('TARGET',axis=1),train['TARGET']

    model = DecisionTreeClassifier()
    model.fit(xtrain,ytrain)

    return model

#let's train the DT model
model = train_model_locally(train_data_sf)

#save the model
import joblib
joblib.dump(model, 'predict_risk_score.joblib')

#upload into the ML_MODELS SNowfla
session.file.put(
    "predict_risk_score.joblib", "@ML_MODELS", auto_compress=False, overwrite=True
)