Instructions to use joddiy/my_awesome_swag_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joddiy/my_awesome_swag_model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultipleChoice tokenizer = AutoTokenizer.from_pretrained("joddiy/my_awesome_swag_model") model = AutoModelForMultipleChoice.from_pretrained("joddiy/my_awesome_swag_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from joddiy/my_awesome_swag_model: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/joddiy/my_awesome_swag_model/resolve/main/training_args.bin
- Command line
-
hf download hf://joddiy/my_awesome_swag_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/joddiy/my_awesome_swag_model/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- 306593a75914e8919249454c79a21c4d4218efb1b859d5ebf8fa219e0ccbf4cd
- Size of remote file:
- 4.6 kB
- SHA256:
- 64f035afbb2bb310705751093e2cf7a24100e2735b78d49ecf35e91639f5fb83
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