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fix typos

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omahs 2023-12-05 09:45:00 +01:00 committed by GitHub
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docs/source/finetuning.md
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@ -21,7 +21,7 @@ them and fine-tune it for your own dataset. This will help you in two main ways:
Fine-tuning comes to the rescue in this case. You can take one of our pre-trained models and fine-tune it on your own Fine-tuning comes to the rescue in this case. You can take one of our pre-trained models and fine-tune it on your own
speech dataset and achieve reasonable results with only a couple of hours of data. speech dataset and achieve reasonable results with only a couple of hours of data.
However, note that, fine-tuning does not ensure great results. The model performance is still depends on the However, note that, fine-tuning does not ensure great results. The model performance still depends on the
{ref}`dataset quality <what_makes_a_good_dataset>` and the hyper-parameters you choose for fine-tuning. Therefore, {ref}`dataset quality <what_makes_a_good_dataset>` and the hyper-parameters you choose for fine-tuning. Therefore,
it still takes a bit of tinkering. it still takes a bit of tinkering.
@ -41,7 +41,7 @@ them and fine-tune it for your own dataset. This will help you in two main ways:
tts --list_models tts --list_models
``` ```
The command above lists the the models in a naming format as ```<model_type>/<language>/<dataset>/<model_name>```. The command above lists the models in a naming format as ```<model_type>/<language>/<dataset>/<model_name>```.
Or you can manually check the `.model.json` file in the project directory. Or you can manually check the `.model.json` file in the project directory.