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:
- ac4d30c580af76da6b17a9a6250e5263cde702badb9a29126ec62dc796991c62
- Size of remote file:
- 4.92 kB
- SHA256:
- 5b643b1cc4fdec24b23924b3d9c8bf8452e1cdd15e0a50c9c9d4f621c74781bb
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