Instructions to use fats-fme/9376c29d-a111-4697-ab9b-d2c2dc35f94a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use fats-fme/9376c29d-a111-4697-ab9b-d2c2dc35f94a 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, "fats-fme/9376c29d-a111-4697-ab9b-d2c2dc35f94a") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5514c4ba13ee261579cef430fd5ef63fd7538557eb0d2fda1c9e9689077f5c43
- Size of remote file:
- 216 MB
- SHA256:
- b39a3de5ab9cb0b904f9adbc584095e75f4d117e736ea409825491bb225ac196
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