Instructions to use Hilbs/FaucetDetect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hilbs/FaucetDetect with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Hilbs/FaucetDetect") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Hilbs/FaucetDetect") model = AutoModelForImageClassification.from_pretrained("Hilbs/FaucetDetect", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc0c1d69884d60fb76dda007ee4fd653efa9a6da74b7d8474006081c8002375d
- Size of remote file:
- 343 MB
- SHA256:
- efc60ed5e083d25f88629d8f1fe0745ab94fbf58e28492cc591b6f22d62767d6
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