Instructions to use igzi/lora-record with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use igzi/lora-record with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3.1-8B") model = PeftModel.from_pretrained(base_model, "igzi/lora-record") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c080c90e58f14b42418fbab21ef9bbddf5da13c2e1aebb18711df24f3fce1d8a
- Size of remote file:
- 5.24 kB
- SHA256:
- 34adb56e91fbcf25d3d67a8fd35e6c03ce5ef0a7d9f9885dc7b1d847436116fe
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.