Instructions to use thangla01/a480a6b7-4d8f-426f-b4d0-70bc6a5fc6a4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use thangla01/a480a6b7-4d8f-426f-b4d0-70bc6a5fc6a4 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-2-7b-chat") model = PeftModel.from_pretrained(base_model, "thangla01/a480a6b7-4d8f-426f-b4d0-70bc6a5fc6a4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0fcbd469c651370c637ca2d925c225a5d36487d543c1bcf808dd4d5dda4f3641
- Size of remote file:
- 6.78 kB
- SHA256:
- 0bdbf36f38d27cda11650764bad9328d0cb7cef0677a6db5d1f3b776fc024182
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