Instructions to use daniel40/8d6e9e4f-e643-4ede-b786-082adcd7c58a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use daniel40/8d6e9e4f-e643-4ede-b786-082adcd7c58a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2") model = PeftModel.from_pretrained(base_model, "daniel40/8d6e9e4f-e643-4ede-b786-082adcd7c58a") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31f0910665e8b3bae8029b8ee266224c6de815a08c4c95f426921f543813854e
- Size of remote file:
- 108 MB
- SHA256:
- 40720c42a0f7c15eedbee84f5058f2c1c0884c86007d72d0e7e8151e84c2fd6d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.