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:
- 578942a78ca39c114a28243bfd043be94eabdbb7b0c5f280b071879bfe091d41
- Size of remote file:
- 16.7 MB
- SHA256:
- 7fa7514a1c67e47cb64d0d808c7940d4ce7653487ac0480d294469af0e7b38b2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.