Instructions to use trangtrannnnn/157b4cb8-2091-4cbe-a7ed-a1fcefb36e7c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use trangtrannnnn/157b4cb8-2091-4cbe-a7ed-a1fcefb36e7c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/mistral-7b-v0.3") model = PeftModel.from_pretrained(base_model, "trangtrannnnn/157b4cb8-2091-4cbe-a7ed-a1fcefb36e7c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c68812b0cc4fd3f7d5ef107272498dc0b445ed933d98f28e3dbf070895ef9125
- Size of remote file:
- 84 MB
- SHA256:
- 38caa9a18dd88b9d57b8be9c842206b283fb46f9c58ecbc96a0aff88637bdbc6
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