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
metadata
license: mit
language:
- en
- zh
pipeline_tag: text-to-speech
tags:
- bert-vits2
- female
- style-bert-vits-jpextra
- tts
- bertvits2
- text-to-speech
- japanese
Download links
・Download model file
・Download confid file
・Download style vectors file
5 JP muluti spearker model
(JP 5 women) + (JP 1 men)
"spk2id": {
"NotAnime-JP-age20female-amazinGood": 0,
"NotAnime-JP-age20female-calmCloud": 1,
"NotAnime-JP-age20female-coolcute": 2,
"NotAnime-JP-age20female-fineCrystal": 3,
"NotAnime-JP-age20male-lightFire": 4
}
"num_styles": 25,
"style2id": {
"Neutral": 0,
"amazinGood(down)": 1,
"amazinGood(lol)": 2,
"amazinGood(onmygod)": 3,
"amazinGood(normal)": 4,
"calmCloud(lol)": 5,
"calmCloud(question)": 6,
"calmCloud(down)": 7,
"calmCloud(hate)": 8,
"calmCloud(ohmygod)": 9,
"calmCloud(normal)": 10,
"coolcute(onmygod)": 11,
"coolcute(normal)": 12,
"coolcute(fine)": 13,
"coolcute(sad)": 14,
"fineCrystal(fine)": 15,
"fineCrystal(ohmygod)": 16,
"fineCrystal(veryfine)": 17,
"fineCrystal(normal)": 18,
"fineCrystal(sad)": 19,
"lightFire(question)": 20,
"lightFire(hello)": 21,
"lightFire(normal)": 22,
"lightFire(strong)": 23,
"lightFire(lol)": 24