Instructions to use npvinHnivqn/phi-2-FCRL-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use npvinHnivqn/phi-2-FCRL-v0.1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/phi-2") model = PeftModel.from_pretrained(base_model, "npvinHnivqn/phi-2-FCRL-v0.1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3db028ced030fedcf109e0ac93d769d5712aa9c818b7283c798a4fe26f4451f1
- Size of remote file:
- 4.93 GB
- SHA256:
- 2f5800c5a84e1440c0096cee41251c2dc6a665e8033c44c3f9f0feb5ea3fe70d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.