Instructions to use kcsteam1/0822_1100step with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kcsteam1/0822_1100step 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, "kcsteam1/0822_1100step") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f438ac5bc1217682fed5de6be893109ffeb05aa1b9b5c8f3c6094ee550489acd
- Size of remote file:
- 26.2 MB
- SHA256:
- 712c058ff9c280455e6a63f1ffbbbb2f918fe43852fb369641cfc2b001a713c3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.