Instructions to use tarabukinivanhome/8e227918-5a73-4542-867a-e82bfd1a23d4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tarabukinivanhome/8e227918-5a73-4542-867a-e82bfd1a23d4 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/OpenHermes-2.5-Mistral-7B") model = PeftModel.from_pretrained(base_model, "tarabukinivanhome/8e227918-5a73-4542-867a-e82bfd1a23d4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a8031fb4e0fc8ad1d34afc205ade8095e03d52b932851ae955a3359dd31181a
- Size of remote file:
- 336 MB
- SHA256:
- 0e880addab117b257599fb9a72fc01393f4ec41748546e5ea07b6d5e9d6e58b5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.