Instructions to use ProDev9515/roadwork-72-NKNVjd9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProDev9515/roadwork-72-NKNVjd9 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProDev9515/roadwork-72-NKNVjd9") 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("ProDev9515/roadwork-72-NKNVjd9") model = AutoModelForImageClassification.from_pretrained("ProDev9515/roadwork-72-NKNVjd9") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_name": "roadwork-snapshot-NKNVjd9", | |
| "description": "Snapshot model", | |
| "version": "1.0.0", | |
| "submitted_by": "5DCNKNVjd9cGYy52N4WND6cayD3hvMW9c24EiKPyMxxBG7cN", | |
| "submission_time": 1750439375 | |
| } |