De-noising Diffusion Probabilistic Model trained on [teticio/audio-diffusion-256](https://huggingface.co/datasets/teticio/audio-diffusion-256) to generate mel spectrograms of 256x256 corresponding to 5 seconds of audio. The code to convert from audio to spectrogram and vice versa can be found in https://github.com/teticio/audio-diffusion along with scripts to train and run inference.
{"tags": ["audio", "spectrograms"], "datasets": ["teticio/audio-diffusion-256"]}
diffusers tensorboard audio spectrograms dataset:teticio/audio-diffusion-256 has_space diffusers:AudioDiffusionPipeline region:us
TAGS
#diffusers #tensorboard #audio #spectrograms #dataset-teticio/audio-diffusion-256 #has_space #diffusers-AudioDiffusionPipeline #region-us 

De-noising Diffusion Probabilistic Model trained on teticio/audio-diffusion-256 to generate mel spectrograms of 256x256 corresponding to 5 seconds of audio. The code to convert from audio to spectrogram and vice versa can be found in URL along with scripts to train and run inference.
TAGS
#diffusers #tensorboard #audio #spectrograms #dataset-teticio/audio-diffusion-256 #has_space #diffusers-AudioDiffusionPipeline #region-us 

passage: TAGS
#diffusers #tensorboard #audio #spectrograms #dataset-teticio/audio-diffusion-256 #has_space #diffusers-AudioDiffusionPipeline #region-us 
