Instructions to use amona-io/house_fault_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amona-io/house_fault_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="amona-io/house_fault_classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("amona-io/house_fault_classification") model = AutoModelForImageClassification.from_pretrained("amona-io/house_fault_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download label_map.json from amona-io/house_fault_classification: direct link, hf CLI and curl.
- Browser
- Download file 222 Bytes
-
https://huggingface.co/amona-io/house_fault_classification/resolve/main/label_map.json
- Command line
-
hf download hf://amona-io/house_fault_classification/label_map.json
-
curl -L -o label_map.json https://huggingface.co/amona-io/house_fault_classification/resolve/main/label_map.json
222 Bytes
| { | |
| "0": "concentrator_broken", | |
| "1": "faultyopening", | |
| "2": "insectscreen_check", | |
| "3": "pedal_malfunction", | |
| "4": "wall_contamination", | |
| "5": "wall_crack", | |
| "6": "wall_peeloff", | |
| "7": "waterleak" | |
| } |