Instructions to use Aivesa/123065a1-9b3c-4f1d-9da6-851c05141cb8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Aivesa/123065a1-9b3c-4f1d-9da6-851c05141cb8 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TitanML/tiny-mixtral") model = PeftModel.from_pretrained(base_model, "Aivesa/123065a1-9b3c-4f1d-9da6-851c05141cb8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9799abab651dd92c44d39f46a3f32f34f02d7e7a468e455ce496eb90b7b8d620
- Size of remote file:
- 7.59 MB
- SHA256:
- f8726b1c336e2d2dff9b9299c5db0a422f048c46b1f75de803abce5b9766f327
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