Instructions to use crncskn/radiovers12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crncskn/radiovers12 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForPreTraining processor = AutoImageProcessor.from_pretrained("crncskn/radiovers12") model = AutoModelForPreTraining.from_pretrained("crncskn/radiovers12", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from crncskn/radiovers12: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/crncskn/radiovers12/resolve/main/training_args.bin
- Command line
-
hf download hf://crncskn/radiovers12/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/crncskn/radiovers12/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- 712e8d074dc468e755838c2d99fe5cfcdb8cffe8d991e718660a500e40162d80
- Size of remote file:
- 5.05 kB
- SHA256:
- 9f612eee7fcbd13173e47f2db6f50ba428e7cf81f0270a4eed967c1cb3a8d0e7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.