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Audio generation using diffusion models, in PyTorch.

Results 16 audio-diffusion-pytorch issues
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Hi, I'm training on a dataset of songs, and I was training with this package. After about 10 epochs (of 1000 samples each) the loss seems to converge, however after...

Hi, I've been playing with this diffusion model library for a few days, it is great to have such library that allows common users to train audio data with limited...

Hi! I have worked with unconditional generation using this fine repo. It is a lot of fun! I will do latent diffusion next. I am already looking forward to it....

the test auido is 32-channel 2**15-length, for the batch 2 Besides, the num of trainable paras of the text condition generationis only 672M when follow the paper setting(text embding dim...

The code shows that a-unet is used to construct the unet, but looking at the a-unet, the unet is constructed in a nested-like structure. So, does this unet have middle...

Hi, Is it possible to do class-conditional generation instead of text-conditioning? Thanks.

This PR adds default args to the construction of the UNet to include dilation and dropout. Details on changes to underlying repo for this to work can be found here:...

Hi, I test the example you gave for conditioning on text, but got error: ``` # Train model with audio waveforms audio_wave = torch.randn(1, 2, 2**18) # [batch, in_channels, length]...

Hi! I am very curious about the future work part of the paper. There were a few suggestions in the paper. Let me talk about two. ## 1. Use perceptual...