Instructions to use nhoxinh/f1f1bb3f-d9e0-4a2d-b663-b43ff01e2944 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhoxinh/f1f1bb3f-d9e0-4a2d-b663-b43ff01e2944 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("teknium/OpenHermes-2.5-Mistral-7B") model = PeftModel.from_pretrained(base_model, "nhoxinh/f1f1bb3f-d9e0-4a2d-b663-b43ff01e2944") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7900c9ae110e55cf25e0caedd9e171392d21d57f61fac0f83d50f088cb422923
- Size of remote file:
- 6.78 kB
- SHA256:
- 0ce975b094debb19c1a637a613a3b1cd5034d50245872b8f9b0414d294750812
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