Instructions to use Pro-aryan00/roberta-mcq-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Pro-aryan00/roberta-mcq-ft with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("roberta-base") model = PeftModel.from_pretrained(base_model, "Pro-aryan00/roberta-mcq-ft") - Transformers
How to use Pro-aryan00/roberta-mcq-ft with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Pro-aryan00/roberta-mcq-ft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37312c3e7bdda80c6163772aefaf4d475d20df47407e029fb13a12ab69b1e5b7
- Size of remote file:
- 5.2 kB
- SHA256:
- 348c4282e2006341628d37f93eee4f8c97f51af58ec43846b05d4fb76fe3abc6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.