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:
- 277e3dce004dfa98177d79435e7122ca74810cf68b00f2be1004f837058b78e7
- Size of remote file:
- 5.59 kB
- SHA256:
- b9b570979fe3321d4de2454f36475c8d35e6fd68b5100ed47a7dc03d542ad2b0
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