Instructions to use nhung03/03e7abef-693d-48b4-a69a-4f628352d9bb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung03/03e7abef-693d-48b4-a69a-4f628352d9bb with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-2-9b") model = PeftModel.from_pretrained(base_model, "nhung03/03e7abef-693d-48b4-a69a-4f628352d9bb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44e914d0b75c0d0a6bfccab2f0eeb41dc8aab5d7ecdafeecc5f23c00384544cd
- Size of remote file:
- 6.78 kB
- SHA256:
- 6166dad20f1b3825aa71fb7d96e4e181aa321d122a5e3809ad90cff12d3b5e77
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