Instructions to use KrithikV/phi-3-mini-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use KrithikV/phi-3-mini-LoRA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-4k-instruct") model = PeftModel.from_pretrained(base_model, "KrithikV/phi-3-mini-LoRA") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d39d43d47d86a2f9ea18f73b44250177228062e61b18a6d916482b49eca049e6
- Size of remote file:
- 5.43 kB
- SHA256:
- 8878f600d4eaa80da8759065d02110b078211820bd1ce796ab6d601701cd3a70
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.