Instructions to use quannh197/5dd5a0fb-0035-4ea8-8e65-beaf15e840a6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use quannh197/5dd5a0fb-0035-4ea8-8e65-beaf15e840a6 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Pro-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "quannh197/5dd5a0fb-0035-4ea8-8e65-beaf15e840a6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a40079dcc75baf58ee221ee4a6a2049d793b9b8ae7ed260c85ecfe312defb8a3
- Size of remote file:
- 6.78 kB
- SHA256:
- 5b1f1466f655e48e0de4e7b832b04df496c4ab9395a089b4087a7fbe84284b24
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.