Instructions to use SHENMU007/neunit_BASE_V10.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SHENMU007/neunit_BASE_V10.3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="SHENMU007/neunit_BASE_V10.3")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("SHENMU007/neunit_BASE_V10.3") model = AutoModelForTextToSpectrogram.from_pretrained("SHENMU007/neunit_BASE_V10.3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e80e07ef37a0eba8db9677410c5410099ac94c8346cbf517ae6426b77da33cf4
- Size of remote file:
- 4.16 kB
- SHA256:
- dc59ae0b522d7b2477f0c266304ce75b323791494590ef70ba780fe8960d44ff
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.