Instructions to use danlou/roberta-large-finetuned-csqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danlou/roberta-large-finetuned-csqa with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultipleChoice tokenizer = AutoTokenizer.from_pretrained("danlou/roberta-large-finetuned-csqa") model = AutoModelForMultipleChoice.from_pretrained("danlou/roberta-large-finetuned-csqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 00c90673f9fb23343016a47c61cf68c0a915e2d63a63aab5de2f7dbbd2038952
- Size of remote file:
- 2.67 kB
- SHA256:
- 8fd604937978614cbcc0cadc28290de65ae67361747ce157745148eb6028a70d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.