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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・<a href="https://huggingface.co/Mofa-Xingche/girl-style-bert-vits2-JPExtra-models/resolve/main/style_vectors.npy?download=true" target="_blank">Download style vectors file</a>
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Style Bert vits2 2.1 JPExtra ,5 JP muluti spearker model<br>
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(JP 5 women) + (JP 1 men) + (26 emotion style...ex sad,happy,lol)<br>
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・<a href="https://huggingface.co/Mofa-Xingche/girl-style-bert-vits2-JPExtra-models/resolve/main/style_vectors.npy?download=true" target="_blank">Download style vectors file</a>
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Style Bert vits2 2.1 JPExtra ,5 JP muluti spearker model(licence MIT)<br>
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(JP 5 women) + (JP 1 men) + (26 emotion style...ex sad,happy,lol)...<b>Abuse prohibited,,滥用禁止,,悪用禁止</b><br>
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