diff --git a/firebase_admin/ml.py b/firebase_admin/ml.py
index 809ba9a41..c6720f081 100644
--- a/firebase_admin/ml.py
+++ b/firebase_admin/ml.py
@@ -524,11 +524,13 @@ def _tf_convert_from_keras_model(keras_model):
             return converter.convert()
 
     @classmethod
-    def from_saved_model(cls, saved_model_dir, bucket_name=None, app=None):
+    def from_saved_model(cls, saved_model_dir, model_file_name='firebase_ml_model.tflite',
+                         bucket_name=None, app=None):
         """Creates a Tensor Flow Lite model from the saved model, and uploads the model to GCS.
 
         Args:
             saved_model_dir: The saved model directory.
+            model_file_name: The name that the tflite model will be saved as in Cloud Storage.
             bucket_name: The name of an existing bucket. None to use the default bucket configured
                 in the app.
             app: Optional. A Firebase app instance (or None to use the default app)
@@ -541,16 +543,18 @@ def from_saved_model(cls, saved_model_dir, bucket_name=None, app=None):
         """
         TFLiteGCSModelSource._assert_tf_enabled()
         tflite_model = TFLiteGCSModelSource._tf_convert_from_saved_model(saved_model_dir)
-        open('firebase_ml_model.tflite', 'wb').write(tflite_model)
-        return TFLiteGCSModelSource.from_tflite_model_file(
-            'firebase_ml_model.tflite', bucket_name, app)
+        with open(model_file_name, 'wb') as model_file:
+            model_file.write(tflite_model)
+        return TFLiteGCSModelSource.from_tflite_model_file(model_file_name, bucket_name, app)
 
     @classmethod
-    def from_keras_model(cls, keras_model, bucket_name=None, app=None):
+    def from_keras_model(cls, keras_model, model_file_name='firebase_ml_model.tflite',
+                         bucket_name=None, app=None):
         """Creates a Tensor Flow Lite model from the keras model, and uploads the model to GCS.
 
         Args:
             keras_model: A tf.keras model.
+            model_file_name: The name that the tflite model will be saved as in Cloud Storage.
             bucket_name: The name of an existing bucket. None to use the default bucket configured
                 in the app.
             app: Optional. A Firebase app instance (or None to use the default app)
@@ -563,9 +567,9 @@ def from_keras_model(cls, keras_model, bucket_name=None, app=None):
         """
         TFLiteGCSModelSource._assert_tf_enabled()
         tflite_model = TFLiteGCSModelSource._tf_convert_from_keras_model(keras_model)
-        open('firebase_ml_model.tflite', 'wb').write(tflite_model)
-        return TFLiteGCSModelSource.from_tflite_model_file(
-            'firebase_ml_model.tflite', bucket_name, app)
+        with open(model_file_name, 'wb') as model_file:
+            model_file.write(tflite_model)
+        return TFLiteGCSModelSource.from_tflite_model_file(model_file_name, bucket_name, app)
 
     @property
     def gcs_tflite_uri(self):