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%2F1/pytorch_model.bin
- Command line
-
hf download hf://Taki3d/CrackDetectionLowRes@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Taki3d/CrackDetectionLowRes/resolve/refs%2Fpr%2F1/pytorch_model.bin
343 MB
- Xet hash:
- 0f231ff5b81dcce733299ce828eb07f38560cd1bf996f344458d7a4c7ebad3db
- Size of remote file:
- 343 MB
- SHA256:
- 2186811f62139aaf2c8ebbf797619b4ade40a2597dfdb3820e0f1a3da1de308a
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