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/main/pytorch_model.bin
- Command line
-
hf download hf://Taki3d/CrackDetectionLowRes/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Taki3d/CrackDetectionLowRes/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- e0c0c111aa044cd54e4bb9bb273a1720bf2c79b0c4100a60402caa25c4bfdf3d
- Size of remote file:
- 343 MB
- SHA256:
- 9119a701dbeeaae9beb0c146d7c901ec0f0b9e35f77b45c81759ebf1f088df21
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