Instructions to use Priyanka-Balivada/LoRA-SemEval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Priyanka-Balivada/LoRA-SemEval with PEFT:
from peft import PeftModel from transformers import AutoModelForTokenClassification base_model = AutoModelForTokenClassification.from_pretrained("bert-base-uncased") model = PeftModel.from_pretrained(base_model, "Priyanka-Balivada/LoRA-SemEval") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Priyanka-Balivada/LoRA-SemEval: direct link, hf CLI and curl.
- Browser
- Download file 4.22 kB
-
https://huggingface.co/Priyanka-Balivada/LoRA-SemEval/resolve/main/training_args.bin
- Command line
-
hf download hf://Priyanka-Balivada/LoRA-SemEval/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Priyanka-Balivada/LoRA-SemEval/resolve/main/training_args.bin
4.22 kB
- Xet hash:
- 3e38501794d7f2d3339af61b9d77eb94c8a77d945c9e0ada11b857bc8cdba13a
- Size of remote file:
- 4.22 kB
- SHA256:
- 961a2a38270a98858b3e458823b9c956232790d2505ed37aeb67cbbcd985e941
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