Instructions to use Saran09577/saran-002-ss with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use Saran09577/saran-002-ss with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("fill-in-model-name") model.load_adapter("Saran09577/saran-002-ss", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Saran09577/saran-002-ss: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/Saran09577/saran-002-ss/resolve/main/training_args.bin
- Command line
-
hf download hf://Saran09577/saran-002-ss/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Saran09577/saran-002-ss/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- 27c062869676c8b407e4ab0371fc8b75283843de9788eed564ec7269d83bf0e8
- Size of remote file:
- 5.24 kB
- SHA256:
- 62b882098dd02bcadd59aacaee9be1aa3ec578e1ceba8ec92046e85bf91d518f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.