Text-to-Speech
Transformers
English
Chinese
bert-vits2
female
style-bert-vits-jpextra
tts
bertvits2
japanese
Instructions to use Mofa-Xingche/girl-style-bert-vits2-JPExtra-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mofa-Xingche/girl-style-bert-vits2-JPExtra-models with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Mofa-Xingche/girl-style-bert-vits2-JPExtra-models")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Mofa-Xingche/girl-style-bert-vits2-JPExtra-models", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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#get audio
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#model files in to C:\Users\YOUR USERNAME\....\Style-Bert-VITS2\model_assets\ =>(NotAnimeJPManySpeaker_e120_s22200.safetensors),(config.json),(style_vectors.npy)
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python \Style-Bert-VITS2\server_fastapi.py
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#get audio
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#model files in to C:\Users\YOUR USERNAME\....\Style-Bert-VITS2\model_assets\NotAnimeJPManySpeaker\ =>(NotAnimeJPManySpeaker_e120_s22200.safetensors),(config.json),(style_vectors.npy)
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python \Style-Bert-VITS2\server_fastapi.py
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