Instructions to use dada22231/0bbbd782-1dff-4ee1-ab35-6143ea1eeac0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/0bbbd782-1dff-4ee1-ab35-6143ea1eeac0 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/codegemma-2b") model = PeftModel.from_pretrained(base_model, "dada22231/0bbbd782-1dff-4ee1-ab35-6143ea1eeac0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 02a97a239350ebf2c6e28bfae1051016de658a987fcdd643f6bb6d349370e5b2
- Size of remote file:
- 157 MB
- SHA256:
- 4ea41541549654ca1855ff788e780b36c7afd3fe2f7cebe810500691983bf52f
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