Instructions to use JoshMe1/sn72 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JoshMe1/sn72 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="JoshMe1/sn72") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("JoshMe1/sn72") model = AutoModelForImageClassification.from_pretrained("JoshMe1/sn72", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_name": "roadwork", | |
| "description": "ViT model for roadwork detection.", | |
| "version": "0.1.0", | |
| "submitted_by": "5C5WdST3VoqPhMvmDmqrjmFeSUU75AUxQmS2crJjAuGxd99m", | |
| "submission_time": "1750195200000" | |
| } |