Instructions to use nblinh63/ac6cad31-49cc-4fb8-bd39-754264aa59fa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nblinh63/ac6cad31-49cc-4fb8-bd39-754264aa59fa 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, "nblinh63/ac6cad31-49cc-4fb8-bd39-754264aa59fa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d91de15468724b4eeb53b5beefee45ad2aa87aa0f7fce8b9e362ebd48b08a279
- Size of remote file:
- 168 MB
- SHA256:
- 62641c3fb0bb690da646db63acd77b8f01d87d137cb8da2871135e01dd67e34e
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