Instructions to use TimKond/diffusion-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TimKond/diffusion-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="TimKond/diffusion-detection") 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("TimKond/diffusion-detection") model = AutoModelForImageClassification.from_pretrained("TimKond/diffusion-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 840122979a2d629adac81dc6ce4539df15af3c59a4079afc745ccab36c7d1f53
- Size of remote file:
- 343 MB
- SHA256:
- 5ca49ae14f393414cabd82707f498157a8a793e8cdedae766e6169edd54203b0
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