Instructions to use predibase/hellaswag_processed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use predibase/hellaswag_processed with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1") model = PeftModel.from_pretrained(base_model, "predibase/hellaswag_processed") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5e9da2598d6f3e3229df5a931d85da40966f9405754664187e879152eab66cd
- Size of remote file:
- 13.6 MB
- SHA256:
- 057866f802b864c13cb0d79df7e7c0a7728e7972bb1253a4a16c84e25d84bdae
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