Instructions to use SHENMU007/neunit_BASE_V10.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SHENMU007/neunit_BASE_V10.5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="SHENMU007/neunit_BASE_V10.5")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("SHENMU007/neunit_BASE_V10.5") model = AutoModelForTextToSpectrogram.from_pretrained("SHENMU007/neunit_BASE_V10.5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da5c43d9b0ddd1bd3086273970e823ad2ba32e724323ee053776e852615981d8
- Size of remote file:
- 4.16 kB
- SHA256:
- 0e5a472538416ec7ec462169de2ae8cd541407aefaa16c6171e689b20c6b0adc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.