Instructions to use aseratus1/4c57a2a2-b835-45a4-9278-d11c09e981f8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aseratus1/4c57a2a2-b835-45a4-9278-d11c09e981f8 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, "aseratus1/4c57a2a2-b835-45a4-9278-d11c09e981f8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e3363281e2f0ca85bc657f05b878a4347e5793616a010d1fdca71da1249b8acb
- Size of remote file:
- 108 MB
- SHA256:
- 70247c00cb9d35774adc8eda1300500c9a5a77e216146c1fad44c21aee27faea
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