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Update app.py
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app.py
CHANGED
@@ -63,12 +63,8 @@ SIDEBAR_INFO = f"""
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</div>
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"""
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# ------------transcribe section------------
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) # chunk_length_s=30, generate_kwargs={'task': 'transcribe', 'language': 'no'}
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@spaces.GPU()
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def transcribe(microphone, file_upload):
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#--------------____________________________________________--------------"
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warn_output = ""
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if (microphone is not None) and (file_upload is not None):
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warn_output = (
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@@ -80,17 +76,18 @@ def transcribe(microphone, file_upload):
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return "ERROR: You have to either use the microphone or upload an audio file"
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file = microphone if microphone is not None else file_upload
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#--------------____________________________________________--------------"
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start_time = time.time()
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#--------------____________________________________________--------------"
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device = "cuda" if torch.cuda.is_available() else "cpu"
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pipe = pipeline("automatic-speech-recognition", model="NbAiLab/nb-whisper-large", device=device)
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text = pipe(file)["text"]
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#--------------____________________________________________--------------"
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end_time = time.time()
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output_time = end_time - start_time
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word_count = len(text.split())
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</div>
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"""
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@spaces.GPU()
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def transcribe(microphone, file_upload):
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warn_output = ""
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if (microphone is not None) and (file_upload is not None):
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warn_output = (
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return "ERROR: You have to either use the microphone or upload an audio file"
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file = microphone if microphone is not None else file_upload
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start_time = time.time()
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+
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#--------------____________________________________________--------------"
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device = "cuda" if torch.cuda.is_available() else "cpu"
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pipe = pipeline("automatic-speech-recognition", model="NbAiLab/nb-whisper-large", device=device)
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# chunk_length_s=30, generate_kwargs={'task': 'transcribe', 'language': 'no'}
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text = pipe(file)["text"]
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#--------------____________________________________________--------------"
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end_time = time.time()
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output_time = end_time - start_time
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word_count = len(text.split())
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