diff --git a/ultralytics/yolo/engine/exporter.py b/ultralytics/yolo/engine/exporter.py
index dc457a0..ababe0c 100644
--- a/ultralytics/yolo/engine/exporter.py
+++ b/ultralytics/yolo/engine/exporter.py
@@ -313,14 +313,11 @@ class Exporter:
         # Simplify
         if self.args.simplify:
             try:
-                cuda = torch.cuda.is_available()
-                check_requirements(('onnxruntime-gpu' if cuda else 'onnxruntime', 'onnx-simplifier>=0.4.1'))
-                import onnxsim  # noqa
+                check_requirements('onnxsim')
+                import onnxsim
 
                 LOGGER.info(f'{prefix} simplifying with onnx-simplifier {onnxsim.__version__}...')
-                model_onnx, check = onnxsim.simplify(model_onnx)
-                assert check, 'assert check failed'
-                onnx.save(model_onnx, f)
+                subprocess.run(f'onnxsim {f} {f}', shell=True)
             except Exception as e:
                 LOGGER.info(f'{prefix} simplifier failure: {e}')
         return f, model_onnx
@@ -460,6 +457,40 @@ class Exporter:
                             iou_thres=0.45,
                             conf_thres=0.25,
                             prefix=colorstr('TensorFlow SavedModel:')):
+
+        # YOLOv5 TensorFlow SavedModel export
+        try:
+            import tensorflow as tf  # noqa
+        except ImportError:
+            check_requirements(f"tensorflow{'' if torch.cuda.is_available() else '-macos' if MACOS else '-cpu'}")
+            import tensorflow as tf  # noqa
+        check_requirements(("onnx", "onnx2tf", "sng4onnx", "onnxsim", "onnx_graphsurgeon"),
+                           cmds="--extra-index-url https://pypi.ngc.nvidia.com ")
+
+        LOGGER.info(f'\n{prefix} starting export with tensorflow {tf.__version__}...')
+        f = str(self.file).replace(self.file.suffix, '_saved_model')
+
+        # Export to ONNX
+        self._export_onnx()
+        onnx = self.file.with_suffix('.onnx')
+
+        # Export to TF SavedModel
+        subprocess.run(f'onnx2tf -i {onnx} --output_signaturedefs -o {f}', shell=True)
+
+        # Load saved_model
+        keras_model = tf.saved_model.load(f, tags=None, options=None)
+
+        return f, keras_model
+
+    @try_export
+    def _export_saved_model_OLD(self,
+                                nms=False,
+                                agnostic_nms=False,
+                                topk_per_class=100,
+                                topk_all=100,
+                                iou_thres=0.45,
+                                conf_thres=0.25,
+                                prefix=colorstr('TensorFlow SavedModel:')):
         # YOLOv5 TensorFlow SavedModel export
         try:
             import tensorflow as tf  # noqa
diff --git a/ultralytics/yolo/engine/model.py b/ultralytics/yolo/engine/model.py
index 6f148ac..7c0bd30 100644
--- a/ultralytics/yolo/engine/model.py
+++ b/ultralytics/yolo/engine/model.py
@@ -52,8 +52,8 @@ class YOLO:
         # Load or create new YOLO model
         {'.pt': self._load, '.yaml': self._new}[Path(model).suffix](model)
 
-    def __call__(self, source):
-        return self.predict(source)
+    def __call__(self, source, **kwargs):
+        return self.predict(source, **kwargs)
 
     def _new(self, cfg: str, verbose=True):
         """
@@ -218,3 +218,4 @@ class YOLO:
         args.pop("name", None)
         args.pop("batch", None)
         args.pop("epochs", None)
+        args.pop("cache", None)