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Update app.py
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app.py
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@@ -8,7 +8,7 @@ from transformers.pipelines.audio_utils import ffmpeg_read
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import tempfile
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import os
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MODEL_NAME = "
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BATCH_SIZE = 8
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FILE_LIMIT_MB = 1000
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YT_LENGTH_LIMIT_S = 3600 # limit to 1 hour YouTube files
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@@ -117,7 +117,7 @@ file_transcribe = gr.Interface(
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outputs="text",
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layout="horizontal",
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theme="huggingface",
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title="Whisper Large
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description=(
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"Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the"
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f" checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files"
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@@ -135,7 +135,7 @@ yt_transcribe = gr.Interface(
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outputs=["html", "text"],
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layout="horizontal",
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theme="huggingface",
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title="Whisper Large
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description=(
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"Transcribe long-form YouTube videos with the click of a button! Demo uses the checkpoint"
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f" [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe video files of"
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import tempfile
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import os
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MODEL_NAME = "openai/whisper-large-v3"
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BATCH_SIZE = 8
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FILE_LIMIT_MB = 1000
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YT_LENGTH_LIMIT_S = 3600 # limit to 1 hour YouTube files
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outputs="text",
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layout="horizontal",
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theme="huggingface",
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title="Whisper Large V3: Transcribe Audio",
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description=(
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"Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the"
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f" checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files"
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outputs=["html", "text"],
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layout="horizontal",
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theme="huggingface",
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title="Whisper Large V3: Transcribe YouTube",
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description=(
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"Transcribe long-form YouTube videos with the click of a button! Demo uses the checkpoint"
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f" [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe video files of"
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