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riffusion-cnet-v2 is a fine-tuned version of Riffusion (created by Seth Forsgren and Hayk Martiros), which is a fine-tuned version of Stable Diffusion for generating spectrograms. We add control to Riffusion through ControlNet, which was developed by Lvmin Zhang and Maneesh Agrawala to add extra control to a SD model. This allows us to solve the task of "audio inpainting", which is not a spatially localized task for spectrograms like it is for images, as the positions of audio stems in a spectrogram are not separable in space.

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Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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