Instructions to use Shaier/BERT_MC_OpenBookQA_from_scratch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shaier/BERT_MC_OpenBookQA_from_scratch with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultipleChoice tokenizer = AutoTokenizer.from_pretrained("Shaier/BERT_MC_OpenBookQA_from_scratch") model = AutoModelForMultipleChoice.from_pretrained("Shaier/BERT_MC_OpenBookQA_from_scratch") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e743fe775a5cb0788a7f0b54ae60bd395a31ec89993f0120c1dff479677bfaf
- Size of remote file:
- 3.31 kB
- SHA256:
- ccdf44ec63cd7b52d76e4f4385ea2d84b2b64fc419e1035a84cbbdd40f1f9225
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.