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:
- 662ad1ad1a57f2e47a4296f27bab97ee2dfb22ea1f8955ead769a7aec7d70fc4
- Size of remote file:
- 25.7 kB
- SHA256:
- 28823bf64b422f055e6fa0ca6c5e8ec2d8669e298e181812502581b79d577fc8
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