Instructions to use gokul8967/Loki-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gokul8967/Loki-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-13b-hf") model = PeftModel.from_pretrained(base_model, "gokul8967/Loki-lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d1396241b6fee052cb0f4d91b1dd0ad463d167ded52ef7f10ebd29ea97b08aa8
- Size of remote file:
- 210 MB
- SHA256:
- 3c58543e2cc6da93d858cde05cf2847c45880846495bdfdbe70755b7d3d6cda6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.