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:
- 91a02711e81c9fa85c0566e1d9dd9fdfb8a060e65a8684ae6be5e4b9ba0ce498
- Size of remote file:
- 105 MB
- SHA256:
- f18fd81fde3dbe66c138fe7852e8ca340d44dc5f4f3880c93351c03c0339e2be
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