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main.py

@@ -42,6 +42,7 @@ def download(url):
     return info["id"] + ".wav"
 
 
+'''
 def asr_mlx(wav_file):
   result = mlx_whisper.transcribe(
     wav_file,
@@ -58,6 +59,8 @@ def asr_cpp(wav_file):
   # print(wav_file)
   whisper.transcribe(wav_file, diarize=True)
   whisper.output(output_csv=True, output_jsn=True, output_lrc=True, output_srt=True, output_txt=True, output_vtt=True, log_score=True)
+'''
+
 
 def asr_fast(wav_file):
   from faster_whisper import WhisperModel
@@ -92,8 +95,8 @@ with gr.Blocks() as demo:
     # fetch video from url, and transcibe to text
     ---
     
-    running very poor server with performance, maybe 1.5x time cost with orignal video processing.
-    try yourself locally if your have macbook with silicon or high performance GPU.
+    running very poor server with performance, maybe 1.5x time cost with orignal video processing.  
+    try yourself locally if your have macbook with silicon or high performance GPU.  
     <https://gist.github.com/yanyaoer/5cc7b0dd6729f306ad3cb740d501cabd#file-0-video2text-py>
 
     """)