Instructions to use nblinh/fcd3320e-2511-4e7b-a81e-8b77b18ba2eb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nblinh/fcd3320e-2511-4e7b-a81e-8b77b18ba2eb 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, "nblinh/fcd3320e-2511-4e7b-a81e-8b77b18ba2eb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e49f1a89724ea84dd7ac82ef114289a3bd25518023d137b88687a064ef4befd6
- Size of remote file:
- 216 MB
- SHA256:
- 2c56271fb1b2aedb9192349bd769da25e531e0e1b7bba9d27702d7704ca37d1c
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