Instructions to use philschmid/Llama-3-70b-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use philschmid/Llama-3-70b-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-70b") model = PeftModel.from_pretrained(base_model, "philschmid/Llama-3-70b-lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef26c96144686c4f1d9a34646ff802101fbdfbab4187a171fe6fbc40c9360e51
- Size of remote file:
- 5.24 kB
- SHA256:
- 9fe85445389561d10e2f46d53f4db3db667b9adfcee10cc5e098697becc4e20c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.