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Download README.md from irow/conditional-audio-diffusion: direct link, hf CLI and curl.
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https://huggingface.co/irow/conditional-audio-diffusion/resolve/main/README.md
- Command line
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hf download hf://irow/conditional-audio-diffusion/README.md
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curl -L -o README.md https://huggingface.co/irow/conditional-audio-diffusion/resolve/main/README.md
897 Bytes
| datasets: | |
| - flexthink/audiomnist | |
| pipeline_tag: text-to-speech | |
| This is a basic audio diffusion model using Unet. I've uploaded the weights and training code. | |
| The sample method of the model is used to generate whatever spoken digit you want. | |
| I used the awesome code provided by HuggingFace audio diffusers to generate Mel-spectrograms which were then used to train the model. | |
| For the model code I used the denoising-diffusion-pytorch repo found at https://github.com/lucidrains/denoising-diffusion-pytorch | |
|     | |
| The images found in the files are sample{epoch}_{sample#}_{digit}.jpg. They also have corresponding audio files. | |
| The audio is VERY quiet, so turn up the speakers to hear better. (Just don't forget to turn it down after!) | |