Instructions to use nhung03/12db730b-e5ec-47ab-bc22-a5ae662472c3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung03/12db730b-e5ec-47ab-bc22-a5ae662472c3 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, "nhung03/12db730b-e5ec-47ab-bc22-a5ae662472c3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8193659aad4dbdf199c3868c375d790b8c4228fdf727a65f856ef5a99dbae13d
- Size of remote file:
- 105 MB
- SHA256:
- 835e05ec3a962c2bb752cf90d9b579e83dca34dffeb05926ed1e5b2f151b42c2
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