Steven Liu
a69754bb87
* start with stable diffusion * fix * finish stable diffusion pipelines * fix path to pipeline output * fix flax paths * fix copies * add up to score sde ve * finish first pass of pipelines * fix copies * second review * align doc titles * more review fixes * final review
38 lines
1.5 KiB
Plaintext
38 lines
1.5 KiB
Plaintext
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# Audio Diffusion
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[Audio Diffusion](https://github.com/teticio/audio-diffusion) is by Robert Dargavel Smith, and it leverages the recent advances in image generation from diffusion models by converting audio samples to and from Mel spectrogram images.
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The original codebase, training scripts and example notebooks can be found at [teticio/audio-diffusion](https://github.com/teticio/audio-diffusion).
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<Tip>
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Make sure to check out the Schedulers [guide](/using-diffusers/schedulers) to learn how to explore the tradeoff between scheduler speed and quality, and see the [reuse components across pipelines](/using-diffusers/loading#reuse-components-across-pipelines) section to learn how to efficiently load the same components into multiple pipelines.
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</Tip>
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## AudioDiffusionPipeline
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[[autodoc]] AudioDiffusionPipeline
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- all
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- __call__
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## AudioPipelineOutput
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[[autodoc]] pipelines.AudioPipelineOutput
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## ImagePipelineOutput
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[[autodoc]] pipelines.ImagePipelineOutput
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## Mel
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[[autodoc]] Mel
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