Instructions to use nhung03/8cb70d03-e02b-40be-b363-2d9ed3b3d9ff with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung03/8cb70d03-e02b-40be-b363-2d9ed3b3d9ff with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Llama-3.2-3B") model = PeftModel.from_pretrained(base_model, "nhung03/8cb70d03-e02b-40be-b363-2d9ed3b3d9ff") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd25ad85304bc83a00e1172bbae299ff0341072b97852c8b6ded5716d8bc2f51
- Size of remote file:
- 48.8 MB
- SHA256:
- 0c4fed4c490c6cc817051e78b0cb333dce52316f96a9248a38cacf97c174229a
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