Instructions to use 0x1202/e0fa7c5d-2783-4018-8d5c-34f40936f7fa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 0x1202/e0fa7c5d-2783-4018-8d5c-34f40936f7fa with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("heegyu/WizardVicuna-open-llama-3b-v2") model = PeftModel.from_pretrained(base_model, "0x1202/e0fa7c5d-2783-4018-8d5c-34f40936f7fa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47ea8b47ca9467d778918a09fcc81e915b641c6013674661d26477f27e8ffa4c
- Size of remote file:
- 102 MB
- SHA256:
- 4caef3788f3c565e373be5a1f9c0719b7a9d5cb25b70139c8780763372d826f5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.