Instructions to use lhong4759/70cf06ca-a476-4602-a516-b28fea6afc32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lhong4759/70cf06ca-a476-4602-a516-b28fea6afc32 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, "lhong4759/70cf06ca-a476-4602-a516-b28fea6afc32") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ca8ff379ad6a93aff20a8f25615c31c3a94341bff9b1bfa9883adf5a22326f5
- Size of remote file:
- 216 MB
- SHA256:
- bcae43445f85b3518b35b1f436e97fd8d2e43e7ea92eb1f71c3c1ed2d1a4848b
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