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 pytorch_model.bin from Taki3d/CrackDetectionLowRes: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/Taki3d/CrackDetectionLowRes/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://Taki3d/CrackDetectionLowRes@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Taki3d/CrackDetectionLowRes/resolve/refs%2Fpr%2F2/pytorch_model.bin
343 MB
- Xet hash:
- 037587aab1286b8123c9c3f066ece1d6a1334e4b1a71930f34fc6291cbb97555
- Size of remote file:
- 343 MB
- SHA256:
- 9633cd34b105527bae0289864aad50e005a32111b8c2008f18d089931fdfd2fa
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