Instructions to use SHENMU007/neunit_BASE_V13.5.4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SHENMU007/neunit_BASE_V13.5.4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="SHENMU007/neunit_BASE_V13.5.4")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("SHENMU007/neunit_BASE_V13.5.4") model = AutoModelForTextToSpectrogram.from_pretrained("SHENMU007/neunit_BASE_V13.5.4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6397f149dc1a7e9736d19f072006c280014dd036e03eed8516a27e0094f4dce1
- Size of remote file:
- 4.16 kB
- SHA256:
- e907f5a779cd8749ab3b2ed671ed2ccc106dd4eca6aae1a507cc0ec13d3052ed
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.