Instructions to use voices/VCTK_British_English_Females with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voices/VCTK_British_English_Females with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="voices/VCTK_British_English_Females")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("voices/VCTK_British_English_Females", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 868c8fbae0833999774e496deeb0811b635d0b117107ca32c17dcc87284b16ea
- Size of remote file:
- 879 Bytes
- SHA256:
- b4caf9fe298e6fbbf1e433d6e212689cc89c1ef89c6962c87ad3e8d40c428789
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.