Instructions to use kvsr/peft-adapter-sequence-classification-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kvsr/peft-adapter-sequence-classification-binary with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("distilbert-base-uncased") model = PeftModel.from_pretrained(base_model, "kvsr/peft-adapter-sequence-classification-binary") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 447005c6cbbcdc1d850e8f831f8f00f81ecd069c83deb8cfa89050c04576a5f9
- Size of remote file:
- 134 MB
- SHA256:
- c225c1a220de45bdc9fdc2f4eb24285a23f5498df67a6bb9a97f07b9978f813b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.