Instructions to use Sham786/tts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sham786/tts with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Sham786/tts", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 84a00d30117d58e3da5b5d0bad332eb9e6573949df02903fdb2e0b55dbbce419
- Size of remote file:
- 1.17 GB
- SHA256:
- ea776fc354eabb70cfae145777153483fad72e3e0c5ea345505ded2231a90ce1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.