Instructions to use trl-lib/OpenHermes-2-Mistral-7B-ipo-beta-0.6-steps-800 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use trl-lib/OpenHermes-2-Mistral-7B-ipo-beta-0.6-steps-800 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, "trl-lib/OpenHermes-2-Mistral-7B-ipo-beta-0.6-steps-800") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b94b19e1181f3d5e6d7c5526e18be2cdd3d1cd7e50cd63b8958ad2d699228cbc
- Size of remote file:
- 168 MB
- SHA256:
- cb920ca61105ab26282746bd092fbfcaa4c7404e23a0cb226daf0478a5dc6d90
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.