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:
- 066e31d58674566e689c97cbd38eeaeedb342d26b3fff2a31bbdf243288c5804
- Size of remote file:
- 6.78 kB
- SHA256:
- b25737d83f978ac96858a6c34d70b88e09faa5d870d837a32a50aa432f98543c
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