Instructions to use developerabu/vits-tts-mnn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use developerabu/vits-tts-mnn with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="developerabu/vits-tts-mnn", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("developerabu/vits-tts-mnn", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0b357a6506771557b730b1b1992a861d8d67124436d7d9e3aa94aeb6af9e571
- Size of remote file:
- 63.4 MB
- SHA256:
- c9e9c41d9674334e80e63082a7606d9e8945248f024a8fdd5295dbe9bc9cb826
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