Instructions to use shibajustfor/6e144f5a-a90b-4c83-a215-776d5f93ce10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shibajustfor/6e144f5a-a90b-4c83-a215-776d5f93ce10 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2") model = PeftModel.from_pretrained(base_model, "shibajustfor/6e144f5a-a90b-4c83-a215-776d5f93ce10") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3df09bc932ef9eff4bf701fdf3762ee3b1763710ea89d3bb0853e4403b596739
- Size of remote file:
- 1.06 kB
- SHA256:
- 859ff0676471245c9481ca25d6d6778d1c7963c39b7877af46bb8ca30a9ead21
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