Instructions to use SHENMU007/neunit_BASE_V10.9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SHENMU007/neunit_BASE_V10.9 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="SHENMU007/neunit_BASE_V10.9")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("SHENMU007/neunit_BASE_V10.9") model = AutoModelForTextToSpectrogram.from_pretrained("SHENMU007/neunit_BASE_V10.9") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df9a0d1ee6f3c4cec359ad53180f54dc196f2ca5bd2cb0bf24b2be7789913fe7
- Size of remote file:
- 4.16 kB
- SHA256:
- d9c931eb447d76175e191571f61760e4a451715639a24ada448aff2c09362ba4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.