Instructions to use amrul-hzz/watermark_detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amrul-hzz/watermark_detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="amrul-hzz/watermark_detector") 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("amrul-hzz/watermark_detector") model = AutoModelForImageClassification.from_pretrained("amrul-hzz/watermark_detector", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3943fadb66c1761034923c7df28a703595ef814f7e54e90294534dbd18e0bb2a
- Size of remote file:
- 4.03 kB
- SHA256:
- 30f7025f518401e6bd8db99340b0d7f495ec7ba9e26347b904f44fd2aea494e3
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