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added title and description
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app.py
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@@ -29,7 +29,13 @@ diffuser_pipeline = diffuser_pipeline.to(device)
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#ββββββββββββββββββββββββββββββββββββββββββββ
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# GRADIO SETUP
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audio_input = gr.Audio(source="microphone", type="numpy")
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image_output = gr.Image()
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@@ -45,5 +51,5 @@ def speech_to_text(audio_sample):
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return output.images[0]
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demo = gr.Interface(fn=speech_to_text, inputs=audio_input, outputs=image_output)
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demo.launch()
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#ββββββββββββββββββββββββββββββββββββββββββββ
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# GRADIO SETUP
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title = "Speech to Diffusion β’ Community Pipeline"
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description = """
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<p style='text-align: center;'>This demo can generate an image from an audio sample using pre-trained OpenAI whisper-small and Stable Diffusion.
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Community examples consist of both inference and training examples that have been added by the community.
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<a href='https://github.com/huggingface/diffusers/tree/main/examples/community#speech-to-image' target='_blank'> Click here for more information about community pipelines </a>
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</p>
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"""
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audio_input = gr.Audio(source="microphone", type="numpy")
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image_output = gr.Image()
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return output.images[0]
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demo = gr.Interface(fn=speech_to_text, inputs=audio_input, outputs=image_output, title=title, description=description)
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demo.launch()
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