Added guidance for training on local machine
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# Train locally
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### Build environment
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0. Make sure you have Python>=3.6, <=3.8;
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0. Make sure you have installed `Python>=3.6, <=3.8`, CMake & C/C++ compilers;
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1. Clone this repository;
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2. Run `pip install -r requirements`;
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3. Install GPU version PyTorch: (Make sure you have CUDA 11.6 or 11.7 installed)
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@@ -98,4 +98,8 @@
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Do replace `{Maximum_epochs}` with your desired number of epochs. Empirically, 100 or more is recommended.
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To view training progress, open a new terminal and `cd` to the project root directory, run `tensorboard --logdir="./OUTPUT_MODEL"`, then visit `localhost:6006` with your web browser.
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12. After training is completed, you can use your model by running:
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`python VC_inference.py --model_dir ./OUTPUT_MODEL/G_latest.pth --share True`
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`python VC_inference.py --model_dir ./OUTPUT_MODEL/G_latest.pth --share True`
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13. To clear all audio data, run:
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```
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rm -rf ./custom_character_voice/* ./video_data/* ./raw_audio/* ./denoised_audio/* ./segmented_character_voice/* long_character_anno.txt short_character_anno.txt
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```
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@@ -26,8 +26,9 @@ Chinese & Japanese:[
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because the original VITS has some dependencies that are difficult to configure.
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See [LOCAL.md](https://github.com/Plachtaa/VITS-fast-fine-tuning/blob/main/LOCAL.md) for local training guide.
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Alternatively, you can perform fine-tuning on [Google Colab](https://colab.research.google.com/drive/1pn1xnFfdLK63gVXDwV4zCXfVeo8c-I-0?usp=sharing)
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### How long does it take?
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1. Install dependencies (3 min)
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