diff --git a/tests/test_python.py b/tests/test_python.py
index 062716dde..7af4c9f40 100644
--- a/tests/test_python.py
+++ b/tests/test_python.py
@@ -26,6 +26,7 @@ from ultralytics.utils import (
     WEIGHTS_DIR,
     WINDOWS,
     checks,
+    is_github_action_running,
 )
 from ultralytics.utils.downloads import download
 from ultralytics.utils.torch_utils import TORCH_1_9
@@ -131,6 +132,7 @@ def test_predict_grey_and_4ch():
 
 @pytest.mark.slow
 @pytest.mark.skipif(not ONLINE, reason="environment is offline")
+@pytest.mark.skipif(is_github_action_running(), reason="No auth https://github.com/JuanBindez/pytubefix/issues/166")
 def test_youtube():
     """Test YOLO model on a YouTube video stream, handling potential network-related errors."""
     model = YOLO(MODEL)
diff --git a/ultralytics/__init__.py b/ultralytics/__init__.py
index 39b0aa64d..51f34eb25 100644
--- a/ultralytics/__init__.py
+++ b/ultralytics/__init__.py
@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-__version__ = "8.2.75"
+__version__ = "8.2.76"
 
 import os
 
diff --git a/ultralytics/nn/autobackend.py b/ultralytics/nn/autobackend.py
index cde35a577..6a1bfc4ab 100644
--- a/ultralytics/nn/autobackend.py
+++ b/ultralytics/nn/autobackend.py
@@ -566,10 +566,6 @@ class AutoBackend(nn.Module):
                     y = [y]
             elif self.pb:  # GraphDef
                 y = self.frozen_func(x=self.tf.constant(im))
-                if (self.task == "segment" or len(y) == 2) and len(self.names) == 999:  # segments and names not defined
-                    ip, ib = (0, 1) if len(y[0].shape) == 4 else (1, 0)  # index of protos, boxes
-                    nc = y[ib].shape[1] - y[ip].shape[3] - 4  # y = (1, 160, 160, 32), (1, 116, 8400)
-                    self.names = {i: f"class{i}" for i in range(nc)}
             else:  # Lite or Edge TPU
                 details = self.input_details[0]
                 is_int = details["dtype"] in {np.int8, np.int16}  # is TFLite quantized int8 or int16 model
@@ -607,6 +603,10 @@ class AutoBackend(nn.Module):
         # for x in y:
         #     print(type(x), len(x)) if isinstance(x, (list, tuple)) else print(type(x), x.shape)  # debug shapes
         if isinstance(y, (list, tuple)):
+            if len(self.names) == 999 and (self.task == "segment" or len(y) == 2):  # segments and names not defined
+                ip, ib = (0, 1) if len(y[0].shape) == 4 else (1, 0)  # index of protos, boxes
+                nc = y[ib].shape[1] - y[ip].shape[3] - 4  # y = (1, 160, 160, 32), (1, 116, 8400)
+                self.names = {i: f"class{i}" for i in range(nc)}
             return self.from_numpy(y[0]) if len(y) == 1 else [self.from_numpy(x) for x in y]
         else:
             return self.from_numpy(y)