Instructions to use dada22231/6f0d2e5b-1d77-4e06-9478-e20bfab370bb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/6f0d2e5b-1d77-4e06-9478-e20bfab370bb 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, "dada22231/6f0d2e5b-1d77-4e06-9478-e20bfab370bb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9fa831a968b906250bcc1de656016f753fd2953e83944fe95bdf22ded1aa9661
- Size of remote file:
- 6.84 kB
- SHA256:
- 30f969d90073ee1e83d47b56be755c1ec095609b713863ecc26fad3152e478eb
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