Update app.py

app.py

@@ -17,11 +17,7 @@ print(f"[SYSTEM] | Using {DEVICE} type compute device.")
 DEFAULT_TASK = "transcribe"
 BATCH_SIZE = 8
 
-# repo = pipeline(task="automatic-speech-recognition", model="deepdml/faster-whisper-large-v3-turbo-ct2", chunk_length_s=30, device=DEVICE)
-
-snapshot_download(repo_id="deepdml/faster-whisper-large-v3-turbo-ct2", local_dir="faster-whisper-large-v3-turbo-ct2", repo_type="model")
-
-repo = WhisperModel("faster-whisper-large-v3-turbo-ct2")
+repo = pipeline(task="automatic-speech-recognition", model="onnx-community/whisper-large-v3-turbo", chunk_length_s=30, device=DEVICE)
 
 css = '''
 .gradio-container{max-width: 560px !important}
@@ -35,13 +31,7 @@ footer {
 def transcribe(input=None, task=DEFAULT_TASK):
     print(input)
     if input is None: raise gr.Error("Invalid input.")
-        
-    segments, info = repo.transcribe(input)
-    for segment in segments:
-        print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
-    print(segments)
-    print(info)
-    # 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 0
 
 def cloud():