Update LOCAL.md
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@@ -94,10 +94,10 @@
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If not, run `python3.8 preprocess_v2.py --languages "{PRETRAINED_MODEL}"`
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Do replace `"{PRETRAINED_MODEL}"` with one of `{CJ, CJE, C}` according to your previous model choice.
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11. Start Training.
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Run `python finetune_speaker_v2.py -m "./OUTPUT_MODEL" --max_epochs "{Maximum_epochs}" --drop_speaker_embed True`
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Run `python finetune_speaker_v2.py -m ./OUTPUT_MODEL --max_epochs "{Maximum_epochs}" --drop_speaker_embed True`
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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 continue training on previous checkpoint, change the training command to: `python finetune_speaker_v2.py -m "./OUTPUT_MODEL" --max_epochs "{Maximum_epochs}" --drop_speaker_embed True --cont True`. Before you do this, make sure you have previous `G_latest.pth` and `D_latest.pth` under `./OUTPUT_MODEL/` directory.
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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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To continue training on previous checkpoint, change the training command to: `python finetune_speaker_v2.py -m ./OUTPUT_MODEL --max_epochs "{Maximum_epochs}" --drop_speaker_embed True --cont True`. Before you do this, make sure you have previous `G_latest.pth` and `D_latest.pth` under `./OUTPUT_MODEL/` directory.
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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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13. To clear all audio data, run:
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