Instructions to use Taki3d/CrackDetectionLowRes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Taki3d/CrackDetectionLowRes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Taki3d/CrackDetectionLowRes") 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("Taki3d/CrackDetectionLowRes") model = AutoModelForImageClassification.from_pretrained("Taki3d/CrackDetectionLowRes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Taki3d/CrackDetectionLowRes: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/Taki3d/CrackDetectionLowRes/resolve/refs%2Fpr%2F2/training_args.bin
- Command line
-
hf download hf://Taki3d/CrackDetectionLowRes@refs/pr/2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Taki3d/CrackDetectionLowRes/resolve/refs%2Fpr%2F2/training_args.bin
4.03 kB
- Xet hash:
- 62b4e0bf5a85b881e6fa78ea9c1ed55b6d90450c2eda15ae41afe65226ac6ec7
- Size of remote file:
- 4.03 kB
- SHA256:
- e061d12e807fda1873dd28dd0ab2790804ed22da04020bf83c0c58ccbe5895db
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