Instructions to use ValasaiChander/debatra-stance-tracker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ValasaiChander/debatra-stance-tracker with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("cross-encoder/nli-deberta-v3-small") model = PeftModel.from_pretrained(base_model, "ValasaiChander/debatra-stance-tracker") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 42c2b9ecfd606554f58dc3c21070eb9c632af7d62897e05110aaabef2385bbea
- Size of remote file:
- 3.59 MB
- SHA256:
- 2493364078eb423afbdbbe0a97b86d0c4a13d3e2421a882b75d4a5a47398f6a5
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