Instructions to use Padu98/ampaphi-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Padu98/ampaphi-2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/phi-2") model = PeftModel.from_pretrained(base_model, "Padu98/ampaphi-2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39223955ac32cb6c733d19a0bcf37b0b855e91f5a6d3e89651aa498ea7b33435
- Size of remote file:
- 4.28 kB
- SHA256:
- 9de061e24f7f46d6dc233ccd263ae1fce7875ef1d4027e0ef742de0f41bdf411
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.