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:
- c501401557755ad17a1bd68ea844eaf9e4c985ca6eff93a3321ea447e9680ef9
- Size of remote file:
- 5.2 kB
- SHA256:
- e2773c5b370842a1fd80b23dc0fc67947efc85858cc9a4d7d29822d56fbb6c10
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.