Update app.py

app.py

@@ -6,16 +6,14 @@ import torch
 from transformers import pipeline
 
 # Pre-Initialize
-DEVICE = "auto"
-if DEVICE == "auto":
-    DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
-print(f"[SYSTEM] | Using {DEVICE} type compute device.")
+DEVICE = -1  # -1 indicates CPU for transformers pipeline
+print("[SYSTEM] | Using CPU type compute device.")
 
 # Variables
 DEFAULT_TASK = "transcribe"
 BATCH_SIZE = 8
 
-repo = pipeline(task="automatic-speech-recognition", model="openai/whisper-large-v3-turbo", chunk_length_s=30, device=DEVICE)
+repo = pipeline(task="automatic-speech-recognition", model="openai/whisper-large-v3-turbo", chunk_length_s=30, device=DEVICE  # Ensures CPU usage)
 
 css = '''
 .gradio-container{max-width: 560px !important}
@@ -26,18 +24,27 @@ footer {
 '''
 
 # Functions
-@spaces.GPU(duration=60)
 def transcribe(input=None, task=DEFAULT_TASK):
     print(input)
-    if input is None: raise gr.Error("Invalid input.")
+    if input is None:
+        raise gr.Error("Invalid input.")
         
-    output = repo(input, batch_size=BATCH_SIZE, generate_kwargs={"task": task}, return_timestamps=True)["text"]
+    output = repo(
+        input,
+        batch_size=BATCH_SIZE,
+        generate_kwargs={"task": task},
+        return_timestamps=True
+    )["text"]
     
     return output
 
 def cloud():
     print("[CLOUD] | Space maintained.")
 
+@spaces.GPU(duration=60)
+def gpu():
+    return
+
 # Initialize
 with gr.Blocks(css=css) as main:
     with gr.Column():