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:
- dd8c53d11de82eba2403aef698cc38c7e9a5b34a4654e9e11335b3909ee24af6
- Size of remote file:
- 108 MB
- SHA256:
- 227b9979f4d7c54478b370a5c84d7313e9628db943d7085a1fa1905bf8133ffc
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