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:
- 3b1e63be65fca7a32d1e9fec7f180b59ae4dab7254e6b7cfbc9100c6684946df
- Size of remote file:
- 343 MB
- SHA256:
- 5e2a8ede3b9568b104dbd4341d0955447fb1260edd8ef18fa1ccc5637db54532
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