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:
- 24c4f23593e6cc0618c3bad39324c144ffdf0642eeb801cb63f07f07b34002d2
- Size of remote file:
- 6.78 kB
- SHA256:
- 37039370facf8ee89b9acfc635769c854c092fb756cf416bc77d90688a9a2e99
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