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:
- 2423484edaa29a93bc821012cbdf695b0c145f878c14ce8929f3584f569d4234
- Size of remote file:
- 7.16 MB
- SHA256:
- dd34fbd947a38d5e2b3eddffb544837a3db24c26d387f9a3daeaf0725df879c0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.