Instructions to use hf-internal-testing/tiny-random-MraForMultipleChoice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MraForMultipleChoice with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultipleChoice tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MraForMultipleChoice") model = AutoModelForMultipleChoice.from_pretrained("hf-internal-testing/tiny-random-MraForMultipleChoice", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d2c2d0d4162aefacc7bdb25aedac8318d5ff4679acebad73d19382c4e607053
- Size of remote file:
- 181 kB
- SHA256:
- 493d51b8344878a865141df670b89872f35f4986bd6ae4e1c331cb00d21b124c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.