Instructions to use beast33/ca1e2a2f-e98c-4d4d-b512-67e8198b14f2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use beast33/ca1e2a2f-e98c-4d4d-b512-67e8198b14f2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-1.1-2b-it") model = PeftModel.from_pretrained(base_model, "beast33/ca1e2a2f-e98c-4d4d-b512-67e8198b14f2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 229995d2b0c06ef606681df0f54302837e82aef210ed4684c380c68ea36cb75f
- Size of remote file:
- 314 MB
- SHA256:
- 235f7300273cf83a7f86c1725605f45008b4200b7034555f49383c8a229cf286
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