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jinzr 2024-02-29 11:09:54 +08:00
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egs/ljspeech/TTS/README.md
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@ -15,6 +15,8 @@ This recipe provides a VITS model trained on the LJSpeech dataset.
Pretrained model can be found [here](https://huggingface.co/Zengwei/icefall-tts-ljspeech-vits-2024-02-28). Pretrained model can be found [here](https://huggingface.co/Zengwei/icefall-tts-ljspeech-vits-2024-02-28).
For tutorial and more details, please refer to the [VITS documentation](https://k2-fsa.github.io/icefall/recipes/TTS/ljspeech/vits.html).
The training command is given below: The training command is given below:
``` ```
export CUDA_VISIBLE_DEVICES=0,1,2,3 export CUDA_VISIBLE_DEVICES=0,1,2,3

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egs/vctk/TTS/README.md
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@ -12,3 +12,4 @@ This recipe provides a VITS model trained on the VCTK dataset.
Pretrained model can be found [here](https://huggingface.co/zrjin/icefall-tts-vctk-vits-2023-12-05), note that this model was pretrained on the Edinburgh DataShare VCTK dataset. Pretrained model can be found [here](https://huggingface.co/zrjin/icefall-tts-vctk-vits-2023-12-05), note that this model was pretrained on the Edinburgh DataShare VCTK dataset.
For tutorial and more details, please refer to the [VITS documentation](https://k2-fsa.github.io/icefall/recipes/TTS/vctk/vits.html).