Instructions to use Organika/sdxl-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Organika/sdxl-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Organika/sdxl-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("Organika/sdxl-detector") model = AutoModelForImageClassification.from_pretrained("Organika/sdxl-detector") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d7863578795ed578d22d8106578c92a18cc0ee2bcb7392a32e017997e218c6ac
- Size of remote file:
- 4.73 kB
- SHA256:
- 2c3b96869fa178d23b082e5a6d9bf48ec5865f979c6391b5ae6571ff0f37b681
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