Instructions to use Hmehdi515/phi-3-medium-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Hmehdi515/phi-3-medium-LoRA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-medium-4k-instruct") model = PeftModel.from_pretrained(base_model, "Hmehdi515/phi-3-medium-LoRA") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af441150608fa8a08611297c10516d91c1ee09855f85189d71c34dfdae75c73c
- Size of remote file:
- 5.37 kB
- SHA256:
- ea79016cf2225a4119b36066f398dacea82c84dea19d36cb2bfb2977d239d3aa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.