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Riffusion-Melodiff-v1

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JanBabela commited on Apr 22, 2023

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 			<h1>Riffusion-Melodiff-v1</h1>
-			<p>Riffusion-Melodiff is simple, but interesting idea, (that I have not seen anywhere else) how to modify your music.</p>
-            <p>Riffusion-Melodiff is built on a top of
               <a href="https://huggingface.co/riffusion/riffusion-model-v1" target="_blank">Riffusion </a>
               model, which is fine-tuned Stable Diffusion model to generate Mel Spectrograms. (Spectrogram is kind of
               visual representation of music by dividing waveforms into frequencies.) Riffusion-Melodiff does not contain new model, there was no new training, nor fine-tunig.
               It uses the same model as Riffusion only in a different way.</p>
-            <p>Riffusion-Melodiff uses Img2Img pipeline from Diffusers library to modify images of Mel Spectrograms to produce cover versions of music. Just upload your audio
               in wav format (if you have audio in a different format, transfer it first to wav by online converter). Then you may use Img2img pipeline from the Diffusers library
               with your prompt, seed and strength. Stregth parameter decides, how much will modified audio relate to initial audio and how much it will relate to the prompt.
               When strength is too low the spectrogram is too similar with original one and we do not receive new modification. When strength is too high, then spectrogram is too
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               <source src="When_the_Saints_long_piano_i2i_flute.wav" type="audio/wav">
                 Your browser does not support the audio element.
             </audio>
-          </p>
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 	<body>
 		<div class="card">
 			<h1>Riffusion-Melodiff-v1</h1>
+			<p><br> Riffusion-Melodiff is simple, but interesting idea, (that I have not seen anywhere else) how to create cover versions from songs.</p>
+            <p><br> Riffusion-Melodiff is built on a top of
               <a href="https://huggingface.co/riffusion/riffusion-model-v1" target="_blank">Riffusion </a>
               model, which is fine-tuned Stable Diffusion model to generate Mel Spectrograms. (Spectrogram is kind of
               visual representation of music by dividing waveforms into frequencies.) Riffusion-Melodiff does not contain new model, there was no new training, nor fine-tunig.
               It uses the same model as Riffusion only in a different way.</p>
+            <p>Riffusion-Melodiff uses Img2Img pipeline from Diffusers library to modify images of Mel Spectrograms to produce new versions of music. Just upload your audio
               in wav format (if you have audio in a different format, transfer it first to wav by online converter). Then you may use Img2img pipeline from the Diffusers library
               with your prompt, seed and strength. Stregth parameter decides, how much will modified audio relate to initial audio and how much it will relate to the prompt.
               When strength is too low the spectrogram is too similar with original one and we do not receive new modification. When strength is too high, then spectrogram is too
               <source src="When_the_Saints_long_piano_i2i_flute.wav" type="audio/wav">
                 Your browser does not support the audio element.
             </audio>
+          </p>
+          <p> <br> Im using standard (not paid) Google Colab Gpu configuration for inference. Im using default values for number of inference steps (23) from the underlying
+            pipelines. With this setup it takes about 8s to produce 5s long modified sample. For start it is ok, I would say.</p>
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