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:
- e42292b0f4cbcc16ab2891717c90be1d952fdc145940fd9bf870522d3d162e06
- Size of remote file:
- 55.5 MB
- SHA256:
- 7b774059a3d91eba9d43657e0eddd567a691032eb2e5cf9263968f6f48551aba
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