Instructions to use mlai-dante/road-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mlai-dante/road-model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-VL-8B-Instruct") model = PeftModel.from_pretrained(base_model, "mlai-dante/road-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da7022b0d1c43d9b7e1d7dd9478e19f1bd1ae7ce99ff503078163393951e1647
- Size of remote file:
- 3.56 MB
- SHA256:
- 2bb1a22cfbe25b8e5a232b7fc4d7fc5073923b45724a5f813b00811bb6620f66
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.