Instructions to use exiort/base-llama with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use exiort/base-llama with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "exiort/base-llama") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b528234b4f1448c356933a0f49b1df0798e4777792221256bad517e4f121ee6e
- Size of remote file:
- 43.1 MB
- SHA256:
- a1919c5a96b69505d240c8ce1f0a2cc477404f0a24cff0717ed3a9d2a47216de
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.