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--- |
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license: mit |
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--- |
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# BigVGAN-L |
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The 24kHz model was pretrained using LibriTTS dataset with a full 100-band mel spectrogram as input (see ```config.json``` for the exact hyperparameter setup) with the [BigVGAN](https://github.com/NVIDIA/BigVGAN) |
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repository. The pretraining was performed over 1300k steps with a 100 batch size with 8 A100 40GB GPUs. |
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# Inference |
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The run the inference with the example command for generating audio from the model. It computes mel spectrograms using wav files from --input_wavs_dir and saves the generated audio to --output_dir. |
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``` |
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python NEMO_PATH/inference.py \ |
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--checkpoint_file MODEL_PATH/BigVGAN-L/g_01300000.pt \ |
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--input_wavs_dir AUDIO_PATH/input_wav \ |
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--output_dir AUDIO_PATH/output_wav |
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``` |
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# Continual finetuning |
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The vocoder can be finetuned further on using the NEMO_PATH/train.py script as the checkpoints save all the optimizer information. |
