Instructions to use predibase/drop_explained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use predibase/drop_explained 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/drop_explained") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65bd5764091ba69b69dd822c400ddccd92343aad49fa6b97aa8bbf233a48c365
- Size of remote file:
- 13.6 MB
- SHA256:
- f3f5eb268ed4efb49f98b87f8cafcea979a075a86383f4bc91c59080e75a0fdd
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