Instructions to use eeeebbb2/1ea23141-f4aa-4c8e-a47a-d119b471314e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/1ea23141-f4aa-4c8e-a47a-d119b471314e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Nous-Hermes-2-Mistral-7B-DPO") model = PeftModel.from_pretrained(base_model, "eeeebbb2/1ea23141-f4aa-4c8e-a47a-d119b471314e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94c738fea56cdafd7fe3832ace1f2b1ef890b64551ef422245947090691395c0
- Size of remote file:
- 336 MB
- SHA256:
- 0e1e22a7c24473ae2ce03415b098f515aeed520202a76c93116fabb734bf0b47
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.