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index.html
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<gradio-lite>
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<gradio-file name="app.py" entrypoint>
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import gradio as gr
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output_image = as_gray(input_image)
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return output_image
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demo = gr.Interface(
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process,
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"image",
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"image",
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examples=["lion.jpg", "logo.png"],
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)
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demo.launch()
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</gradio-file>
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<gradio-lite>
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<gradio-file name="app.py" entrypoint>
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import gradio as gr
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from transformers_js_py import pipeline
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pipe = await pipeline('automatic-speech-recognition')
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demo = gr.Interface.from_pipeline(pipe)
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demo.launch()
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</gradio-file>
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