V2.0.0
我们将在这个版本整合 so-vits-svc, 因此, 会有很多大改动.
We will integrate so-vits-svc in this version. Therefore, there are many breaking changes.
我们发布了一个 Content Vec 的预训练模型
We released a Content Vec pre-trained model.
我们强烈建议您参考随附的配置进行微调. 它应用了大量的新功能.
We strongly recommend you refer to the attached config for finetuning. It applied lots of new functions.
Model Info
- Dataset Size: ~100 hours, ~100 singers (M4Singer, OpenSinger, OpenCpop, and In-House Data), 1.5x data aug
- Vocoder: NSF HifiGAN 44.1 khz (OpenVPI)
- Feature Extractor: ContentVec
- MD5: 64034133bdf05910210f2f08cbda65c6
- Steps: 300k on a 2x3090 server
2023-03-17 更新:
我们完成了 FishAudio 稳定版声码器的训练和试验, 该声码器在 60-1200 Hz 表现良好. 经验证, 完全可以作为 OpenVPI 声码器的上位替代.
We finished the training and testing of FishAudio stable vocoder (based on NSF-HiFiGAN), and it works well between 60 to 1200 Hz. Now, it will be the replacement of the original OpenVPI NSF-HiFiGAN vocoder.
使用方法: 下载 nsf_hifigan-stable-v1.zip 解压到 checkpoints
How to use: Download and decompress nsf_hifigan-stable-v1.zip
to checkpoints
为了更方便用户使用, 我们还增加了 OpenUTAU vocoder: nsf_hifigan-stable-v1.dsvocoder
.
For convenience, we also attached an OpenUTAU vocoder: nsf_hifigan-stable-v1.dsvocoder
.
本模型根据 CC-BY-NC-SA 4.0 license 发布, 下载前请仔细阅读.
This model is released under CC-BY-NC-SA 4.0 license, please read it before you download.