diff --git a/controllable_talknet.py b/controllable_talknet.py
index ddfb687..4a5aa01 100644
--- a/controllable_talknet.py
+++ b/controllable_talknet.py
@@ -24,7 +24,7 @@
 from core.download import download_from_drive, download_reconst
 
 app = JupyterDash(__name__)
-DEVICE = "cuda:0"
+DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 CPU_PITCH = False
 RUN_PATH = os.path.dirname(os.path.realpath(__file__))
 if RUN_PATH == "/content":
diff --git a/core/extract.py b/core/extract.py
index 09bb16a..266aa1a 100644
--- a/core/extract.py
+++ b/core/extract.py
@@ -397,6 +397,7 @@ def _torchcrepe_f0(self, wav_path, hop_length=256):
         audio_numpy = audio.squeeze(0).numpy()
         audio_x = np.arange(0, len(audio_numpy)) / 22050.0
 
+        device = "cuda" if torch.cuda.is_available() else "cpu"
         frequency, confidence = torchcrepe.predict(
             audio,
             sr,
@@ -407,7 +408,7 @@ def _torchcrepe_f0(self, wav_path, hop_length=256):
             decoder=torchcrepe.decode.viterbi,
             return_periodicity=True,
             batch_size=128,
-            device="cuda:0",
+            device=device,
         )
         confidence = torchcrepe.filter.median(confidence, 3)
 
diff --git a/mycroft_talknet.py b/mycroft_talknet.py
index d94eb8e..fe4d601 100644
--- a/mycroft_talknet.py
+++ b/mycroft_talknet.py
@@ -19,7 +19,7 @@
 
 app = Flask(__name__)
 RUN_PATH = os.path.dirname(os.path.realpath(__file__))
-DEVICE = "cuda:0"
+DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 
 
 def load_hifigan(model_name, conf_name):