Instructions to use nhung03/382bce09-54c8-42a5-8974-235c3735a241 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung03/382bce09-54c8-42a5-8974-235c3735a241 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("lmsys/vicuna-7b-v1.3") model = PeftModel.from_pretrained(base_model, "nhung03/382bce09-54c8-42a5-8974-235c3735a241") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7add4fb337b6a983db71f594a953c42977ac855f00914099cf941d2647d46c91
- Size of remote file:
- 80.1 MB
- SHA256:
- 7faab14d0850a98e8425580e767575523e8807f816d286e3a93973679ab43ba3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.