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%2F1/training_args.bin
- Command line
-
hf download hf://Taki3d/CrackDetectionLowRes@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Taki3d/CrackDetectionLowRes/resolve/refs%2Fpr%2F1/training_args.bin
4.03 kB
- Xet hash:
- 94864870d5fe7295d4f1a25c69f5ee752822c818a79ebc6cdeca9d22afd6e165
- Size of remote file:
- 4.03 kB
- SHA256:
- ee39ff27081aa8fdb1c8d3dedb3fcc41993515733d25dea3cb64ed2704650a91
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