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  1. app.py +10 -4
app.py CHANGED
@@ -117,10 +117,16 @@ if __name__ == "__main__":
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  )
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  gr.HTML(
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  f"""
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- Speed comparison between <a href="https://huggingface.co/openai/whisper-large-v2"> Whisper</a>
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- and <a href="https://huggingface.co/distil-whisper/distil-large-v2"> Distil-Whisper</a>. Both models use the <a href="https://huggingface.co/distil-whisper/distil-large-v2#long-form-transcription"> chunked long-form transcription algorithm</a>
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- in 🤗 Transformers with Flash Attention support. To ensure fair usage of the Space, we ask that audio
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- file inputs are kept to < 30 mins.
 
 
 
 
 
 
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  """
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  )
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  audio = gr.components.Audio(type="filepath", label="Audio input")
 
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  )
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  gr.HTML(
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  f"""
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+ <a href="https://huggingface.co/distil-whisper/distil-large-v2"> Distil-Whisper</a> is a distilled variant
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+ of the <a href="https://huggingface.co/openai/whisper-large-v2"> Whisper</a> model by OpenAI. Compared to Whisper,
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+ Distil-Whisper runs 6x faster with 50% fewer parameters, while performing to within 1% word error rate (WER) on
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+ out-of-distribution evaluation data.
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+
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+ In this demo, we perform a speed comparison between Whisper and Distil-Whisper in order to test this claim.
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+ Both models use the <a href="https://huggingface.co/distil-whisper/distil-large-v2#long-form-transcription"> chunked long-form transcription algorithm</a>
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+ in 🤗 Transformers, as well as Flash Attention. To use Distil-Whisper yourself, check the code examples on the
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+ <a href="https://github.com/huggingface/distil-whisper#1-usage"> Distil-Whisper repository</a>. To ensure fair
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+ usage of the Space, we ask that audio file inputs are kept to < 30 mins.
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  """
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  )
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  audio = gr.components.Audio(type="filepath", label="Audio input")