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
- Xet hash:
- 863589593b8e26cbf1d80547d9635a5e483516647fb3cdca38096a1cf745ce4f
- Size of remote file:
- 251 MB
- SHA256:
- 37cc6704519dcf5968d1b2a0f25dd5dd2658fbc4f070cd931ba2784508907246
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