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:
- a446a11f0c45e1b2c1d72f4884445d2ffe60228920154a3b8a91c383c0048931
- Size of remote file:
- 336 MB
- SHA256:
- 0732a89aad87e4b5832b5ac0791b75105e96eb4e070ba1c83447440a0c8c5678
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