Instructions to use AXERA-TECH/VoxCPM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AXERA-TECH/VoxCPM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="AXERA-TECH/VoxCPM")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AXERA-TECH/VoxCPM", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 06d257ca2448e6cd5e44d687490a586e5c9787bc444eb3f3689806266ca55381
- Size of remote file:
- 16.7 MB
- SHA256:
- b6be933caaab09678d42dde354d984403e85a7bc4144b4963bcbfa2feecdcbbd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.