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:
- 327538a98ef065c2a65194c531d2a7d3925357f07078307aea3b68e3a921f3a6
- Size of remote file:
- 6.78 kB
- SHA256:
- 0a997fc1eb40d2e45990accead6858393f9755a8a1f5211dd4e57bac2fd8e447
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