Instructions to use eeeebbb2/d4e9b050-e8f3-4296-87c5-18730bfd1b2f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/d4e9b050-e8f3-4296-87c5-18730bfd1b2f with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Meta-Llama-3.1-8B") model = PeftModel.from_pretrained(base_model, "eeeebbb2/d4e9b050-e8f3-4296-87c5-18730bfd1b2f") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e56cad9ac2a38f4b7de211953881b613c19e51838c05adf8f7984c139c2e8f5
- Size of remote file:
- 17.2 MB
- SHA256:
- 6b9e4e7fb171f92fd137b777cc2714bf87d11576700a1dcd7a399e7bbe39537b
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