Instructions to use Harit10/Llama2-PII_final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Harit10/Llama2-PII_final with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "Harit10/Llama2-PII_final") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d8045793c3db8a2ae8019b0d77fd7c5544e2a00276ed853561b445319df8f7c
- Size of remote file:
- 4.92 kB
- SHA256:
- 7a08b993ed454f982ad2fe1b0ae9f804f737ec6b219d3dbbbe50e078fe4a46f1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.