Instructions to use alphacep/vosk-vc-ru with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alphacep/vosk-vc-ru with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("alphacep/vosk-vc-ru", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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pipeline_tag: audio-to-audio
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---
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<https://github.com/alphacep/vosk-tts/tree/master/vc>
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<https://github.com/quickvc/QuickVC-VoiceConversion>
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pipeline_tag: audio-to-audio
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---
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# About
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This is a basic zero-shot voice conversion model trained with VITS + softhubert
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See:
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<https://github.com/alphacep/vosk-tts/tree/master/vc>
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<https://github.com/quickvc/QuickVC-VoiceConversion>
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# Speaker Similarity
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Computed with eval.py with Resemblyzer
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```
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Original QuickVC (trained on VCTK) Average: 0.667 Min: 0.477
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New model Average: 0.836 Min: 0.692
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```
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