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README.md
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The corpus consists of a single speaker, with 4515 segments extracted from [this](https://librivox.org/egri-csillagok-by-geza-gardonyi/) single LibriVox audiobook. It consists about 10 hours of audio data.
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## Training
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The model was trained on a single RTX 3090 GPU
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## Usage
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The model can be used with [JayWalnut's git repo](https://github.com/jaywalnut310/vits), but you have to modify the `text/cleaners.py` file to contain our `hungarian_cleaners` method.
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We provided the necessary files in our repo to do so.
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The corpus consists of a single speaker, with 4515 segments extracted from [this](https://librivox.org/egri-csillagok-by-geza-gardonyi/) single LibriVox audiobook. It consists about 10 hours of audio data.
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## Training
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The model was trained on a single RTX 3090 GPU for 3 days, 200K steps with a batchsize of 16.
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We saved some checkpoints with the optimizers, so the model could be train further, however we didn't notice any noticable effect after step 150K.
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## Usage
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The model `diana_final.pth` can be used with [JayWalnut's git repo](https://github.com/jaywalnut310/vits), but you have to modify the `text/cleaners.py` file to contain our `hungarian_cleaners` method.
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We provided the necessary files in our repo to do so.
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