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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c37b28c1cca0c1614ee440d87602498f41255e46bf0176e1da9199958805cc23
- Size of remote file:
- 37.6 kB
- SHA256:
- 92e46ec3a4a968a76543e6b9e8e6e3698c43d355b0e34459bce0ef9084e68591
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.