Instructions to use voices/VCTK_European_English_Males with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voices/VCTK_European_English_Males with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="voices/VCTK_European_English_Males")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("voices/VCTK_European_English_Males", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7614c2f5844cebd06f0b1d1866a5a4254aa7926752aa8914774bb7b2be45620
- Size of remote file:
- 44.6 MB
- SHA256:
- 8f96efb20cbeeefd81fd8336d7f0155bf8902f82f9474e58ccb19d9e12345172
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.