Instructions to use adammandic87/05cfff3b-1b2a-4ade-b097-dc637d2cd1d5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use adammandic87/05cfff3b-1b2a-4ade-b097-dc637d2cd1d5 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("MLP-KTLim/llama-3-Korean-Bllossom-8B") model = PeftModel.from_pretrained(base_model, "adammandic87/05cfff3b-1b2a-4ade-b097-dc637d2cd1d5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 25d35f51d45b1bb50e911127a474bcaf04053be94057a6d6d7db5ec656f78467
- Size of remote file:
- 84 MB
- SHA256:
- cb1ddca67488148dfb23563adc01176b43327f962a15bfab45ca4e3be37bb0af
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