HF page: https://huggingface.co/SimplCup/RefineGanVCTKV1
RefineGan model trained for Applio RVC on VCTK-Corpus v0.92 (mic1 variant) dataset.
- 177 epochs
- 1180590 steps
- dataset length: 35 hours
- sample rate: 44.1k
To use this model you'll need to download the latest version of Applio (https://github.com/IAHispano/Applio/tree/main) This is a first version of such model, so expect inconsistencies in training small models. Future improvements are coming with the next versions.
This is my first attempt at training a new pretrain for RefineGan vocoder. The model is severely undertrained so to make a good sounding model you'll need a pretty big dataset, minimum 10 minutes but the more the better (i personally recommend at least 20 minutes of clean speech) and train the models to minimum 400 epochs.
How to use:
- download the weights and put them in pretrained_custom folder.
- in "Training" tab change from RVC to Applio, then choose 44.1k sample and RefineGan vocoder.
- In "Training" window open advanced settings, enable custom pretraineds, and choose the G and D weights.



