Instructions to use shibajustfor/5a67588d-8c19-4508-a315-f804ea005cef with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shibajustfor/5a67588d-8c19-4508-a315-f804ea005cef with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/workspace/input_data/NousResearch/Yarn-Mistral-7b-128k") model = PeftModel.from_pretrained(base_model, "shibajustfor/5a67588d-8c19-4508-a315-f804ea005cef") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e090c2d2774ea7875da72d682c12600bd69085e9c28674b917a49fe82ccffe2
- Size of remote file:
- 493 kB
- SHA256:
- dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
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