Instructions to use nhunglaaaaaaa/aedd1742-0ec5-4d24-bc8b-3cb237ec53bb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhunglaaaaaaa/aedd1742-0ec5-4d24-bc8b-3cb237ec53bb with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Yarn-Mistral-7b-128k") model = PeftModel.from_pretrained(base_model, "nhunglaaaaaaa/aedd1742-0ec5-4d24-bc8b-3cb237ec53bb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 32726c94d96b1a5c442963faa3a900decf397fe67b5c530097a9f8b2506c63b6
- Size of remote file:
- 493 kB
- SHA256:
- dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
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