Instructions to use Somalitts/8aad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Somalitts/8aad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="Somalitts/8aad")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("Somalitts/8aad") model = AutoModelForTextToSpectrogram.from_pretrained("Somalitts/8aad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Somalitts/8aad: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/Somalitts/8aad/resolve/main/training_args.bin
- Command line
-
hf download hf://Somalitts/8aad/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Somalitts/8aad/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- 15b0e405770e64709d8a90133c110238d653ae6f6e668dc6bb39688c58bff49a
- Size of remote file:
- 5.43 kB
- SHA256:
- 1ce25110132149446d385a0513480b73b18399d7afadd1a8095dc5f5769a1e94
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.