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39a196c
1
Parent(s):
a66e2eb
fix readme + markdown
Browse files- app.py +25 -3
- banner.png +0 -0
app.py
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@@ -30,16 +30,38 @@ def generate_waveform(description):
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else:
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return "Error: Failed to generate the waveform."
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# gradio interface
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iface = gr.Interface(
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fn=generate_waveform,
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inputs=gr.Textbox(lines=2, placeholder="Enter a music description here..."),
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outputs=gr.Audio(label="Download the Music 🎼"),
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title="Flux Music Diffusion Pipeline",
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description="Enter a music description, and the model will generate a corresponding audio waveform. Download the output as 'awesome.wav'.",
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examples=[
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["
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["
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],
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cache_examples=True
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)
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else:
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return "Error: Failed to generate the waveform."
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intro = """
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# 🎶 OpenMusic: AI-Powered Music Diffusion 🎶
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Welcome to **OpenMusic**, a next-gen diffusion model designed to generate high-quality audio from text descriptions!
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Simply enter a description of the music you'd like to hear, and our AI will generate it for you.
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---
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### Powered by:
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- [GitHub Repository](https://github.com/ivcylc/qa-mdt) by [@changli](https://github.com/ivcylc) 🎓.
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- Introduced in this [Paper](https://arxiv.org/pdf/2405.15863)
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- Hugging Face Diffusers Implementation 🧨 (Super easy to use): [Model](https://huggingface.co/jadechoghari/qa_mdt) by [@jadechoghari](https://github.com/jadechoghari) 🤗.
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---
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"""
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# gradio interface
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iface = gr.Interface(
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description=intro,
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fn=generate_waveform,
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inputs=gr.Textbox(lines=2, placeholder="Enter a music description here..."),
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outputs=gr.Audio(label="Download the Music 🎼"),
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description="Enter a music description, and the model will generate a corresponding audio waveform. Download the output as 'awesome.wav'.",
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examples=[
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["A modern synthesizer creating futuristic soundscapes."],
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["Acoustic ballad with heartfelt lyrics and soft piano."]
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],
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cache_examples=True
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)
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banner.png
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