Instructions to use eeeebbb2/e259bfcb-1b8d-41e0-bc8b-2b5147ec7689 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/e259bfcb-1b8d-41e0-bc8b-2b5147ec7689 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/codegemma-7b-it") model = PeftModel.from_pretrained(base_model, "eeeebbb2/e259bfcb-1b8d-41e0-bc8b-2b5147ec7689") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 75acb08b96fe861a82764a4e150d5c6d700f90723d3a9c5d9d508eb52b36d1b2
- Size of remote file:
- 34.4 MB
- SHA256:
- d964a2c8346d40f95791533eae48730d5f163c2e65fd16333560fd3e661df318
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