Instructions to use JUNGU/qlora-koalpaca-polyglot-12.8b-50step with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use JUNGU/qlora-koalpaca-polyglot-12.8b-50step with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("beomi/polyglot-ko-12.8b-safetensors") model = PeftModel.from_pretrained(base_model, "JUNGU/qlora-koalpaca-polyglot-12.8b-50step") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61e1d174163cc2a83ca7d399ff71d066350d4693d79c12ef198e889c24fa6cf8
- Size of remote file:
- 26.2 MB
- SHA256:
- 5c3c83f23ea8a8250e42fdd3fd2ffbb14ff90b1ac38403ebfa1c30bc107af48c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.