Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -104,32 +104,32 @@ with gr.Blocks() as file:
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submit_button.click(transcribe, [input_audio_microphone, output], [output, latency_textbox], concurrency_limit=None)
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clear_button.click(clear, outputs=[output])
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with gr.Blocks() as translate:
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with gr.Blocks() as demo:
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gr.TabbedInterface([microphone,
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demo.launch()
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submit_button.click(transcribe, [input_audio_microphone, output], [output, latency_textbox], concurrency_limit=None)
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clear_button.click(clear, outputs=[output])
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# with gr.Blocks() as translate:
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# with gr.Column():
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# gr.Markdown(f"# Realtime Whisper Large V3 Turbo (Translation): \n Transcribe and Translate Audio in Realtime. This Demo uses the Checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers.\n Note: The first token takes about 5 seconds. After that, it works flawlessly.")
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# with gr.Row():
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# input_audio_microphone = gr.Audio(streaming=True)
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# output = gr.Textbox(label="Transcription and Translation", value="")
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# latency_textbox = gr.Textbox(label="Latency (seconds)", value="0.0", scale=0)
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# target_language_dropdown = gr.Dropdown(
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# choices=["english", "french", "hindi", "spanish", "russian"],
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# label="Target Language",
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# value="<|es|>"
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# )
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# with gr.Row():
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# clear_button = gr.Button("Clear Output")
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# input_audio_microphone.stream(
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# translate_and_transcribe,
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# [input_audio_microphone, output, target_language_dropdown],
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# [output, latency_textbox],
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# time_limit=45,
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# stream_every=2,
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# concurrency_limit=None
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# )
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# clear_button.click(clear, outputs=[output])
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with gr.Blocks() as demo:
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gr.TabbedInterface([microphone, file], ["Microphone", "Transcribe from file"])
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demo.launch()
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