Instructions to use SHENMU007/neunit_BASE_V7.6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SHENMU007/neunit_BASE_V7.6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="SHENMU007/neunit_BASE_V7.6")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("SHENMU007/neunit_BASE_V7.6") model = AutoModelForTextToSpectrogram.from_pretrained("SHENMU007/neunit_BASE_V7.6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0306ce9a2c10a8ce7685a5fc8db6c9e0c0a9d29ebf01110480b4b21ef42f2d03
- Size of remote file:
- 4.16 kB
- SHA256:
- 8509e91b362da831b3d72ca680d00eeb4b44a658f7bce56452fc799dd4dfa79d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.