Instructions to use banghua/openhermes-dpo-ckpt9k5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use banghua/openhermes-dpo-ckpt9k5 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("teknium/OpenHermes-2.5-Mistral-7B") model = PeftModel.from_pretrained(base_model, "banghua/openhermes-dpo-ckpt9k5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 17086d1042212d2d3e8d92e94b02133274eada8e79bd280e96ad5bbef85f92de
- Size of remote file:
- 21.7 kB
- SHA256:
- 569e3f96e00ce6f71c26359f4c3d353fdf576b977f9f1713b440b0de9fb09ce8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.