Instructions to use CDIALing/pidgin-baseline-vits with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CDIALing/pidgin-baseline-vits with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="CDIALing/pidgin-baseline-vits")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("CDIALing/pidgin-baseline-vits") model = AutoModelForTextToWaveform.from_pretrained("CDIALing/pidgin-baseline-vits", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f668760b22b86d90bf34badd26754af51a39230d1869b08356498598c4ec371
- Size of remote file:
- 145 MB
- SHA256:
- 00eea90dbcca74f694d59cbe4dbf81b308d98e2d27bd8152ffafd68df9afa25a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.