Instructions to use marialvsantiago/053abcdf-3e57-498e-a841-b4fd75479bda with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use marialvsantiago/053abcdf-3e57-498e-a841-b4fd75479bda with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/codegemma-2b") model = PeftModel.from_pretrained(base_model, "marialvsantiago/053abcdf-3e57-498e-a841-b4fd75479bda") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 665cb9ccf1eec5b5a49d9552a5c8d598b7e063a0352248df6416eabd49739a08
- Size of remote file:
- 78.5 MB
- SHA256:
- 40b4893a7732b728ee854b95180b274032d0c8fbebbe1850900c16e3c37c7727
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