Instructions to use dimasik87/d92da16d-68e1-4598-a7e3-378a0232bf0a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik87/d92da16d-68e1-4598-a7e3-378a0232bf0a 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, "dimasik87/d92da16d-68e1-4598-a7e3-378a0232bf0a") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8859806b4d16a3440ff87ff18793d7cf7948e742c41ce242311fb0f70fb023e
- Size of remote file:
- 216 MB
- SHA256:
- 6b989deff64bff1ab48f749e4d9aad73c28b9fd0930af8dd5dc634f2f0dc9d7a
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