Comments (4)
I'm guessing you used HuBERT base, if not, please tell me which model you used, so i can correct it in the readme.
i have not noticed any overtraining on 23 epochs, but the 23 epoch model is larger in filesize, so the default is the smaller model. Results are noticably better though.
Cool GUI, i personally use my own GUI
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@C0untFloyd Do you use hubert_base_ls960.pt for German?
from bark-voice-cloning-hubert-quantizer.
Yes I did 👍
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@C0untFloyd how is the voice clone effect?
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Related Issues (20)
- Switch fairseq dependency to transformers' Hubert HOT 1
- issues in notebook due to fairseq version HOT 2
- RuntimeError: The size of tensor a (28) must match the size of tensor b (33) at non-singleton dimension 2
- `KeyError: 'best_loss'` when testing self-trained model HOT 2
- HTTPError: 404 Client Error: Not Found for url: https://huggingface.co/GitMylo/bark-voice-cloning/resolve/main/japanese-HuBERT-quantizer_24_epoch.pth HOT 1
- german-HuBERT-quantizer_14_epoch.pth does not have all meta data HOT 2
- Omni-Lingual Quantizer? HOT 2
- adding batches to training?
- Support for Turkish langauge
- No module named 'hubert' HOT 1
- [Question] This notebook it's for create a speark with trained semantic model?
- How To Train Chinese Tokenizer
- How to create a quantizer in a dialect that Bark didn't support? HOT 2
- Request: Write a tutorial for training quantizers
- Added improved functionality and RestAPI
- Stuck on `Installing Demucs`
- How to Train for Non-Verbal Effects Voice? HOT 2
- Torch compile errors on windows 11
- Support for Swahili Language
- Turkish language support HOT 4
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