diff --git a/tortoise/api.py b/tortoise/api.py
index 01bcc48..df75a80 100755
--- a/tortoise/api.py
+++ b/tortoise/api.py
@@ -236,13 +236,6 @@ def classify_audio_clip(clip):
     results = F.softmax(classifier(clip), dim=-1)
     return results[0][0]
 
-def load_checkpoint(filepath, device):
-    assert os.path.isfile(filepath)
-    print("Loading '{}'".format(filepath))
-    checkpoint_dict = torch.load(filepath, map_location=device)
-    print("Complete.")
-    return checkpoint_dict
-
 class TextToSpeech:
     """
     Main entry point into Tortoise.
@@ -312,10 +305,9 @@ class TextToSpeech:
         self.cvvp = None # CVVP model is only loaded if used.
 
         if use_bigvgan:
-            # credit https://github.com/deviandiceto / https://git.ecker.tech/mrq/ai-voice-cloning/issues/52
+            # credit to https://github.com/deviandice / https://git.ecker.tech/mrq/ai-voice-cloning/issues/52
             self.vocoder = BigVGAN().cpu()
-            state_dict_bigvgan = load_checkpoint(get_model_path('bigvgan_base_24khz_100band.pth', models_dir), self.device)
-            self.vocoder.load_state_dict(state_dict_bigvgan['generator'])
+            self.vocoder.load_state_dict(torch.load(get_model_path('bigvgan_base_24khz_100band.pth', models_dir), map_location=torch.device('cpu'))['generator'])
         else:
             self.vocoder = UnivNetGenerator().cpu()
             self.vocoder.load_state_dict(torch.load(get_model_path('vocoder.pth', models_dir), map_location=torch.device('cpu'))['model_g'])