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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 40eff1a0ca0b55ea84d45820a49c9a5d369f566cfa35fc0d14a88971d7d5e564
- Size of remote file:
- 343 MB
- SHA256:
- e554680f89718a2799e46155918632c013209fb8734bf1906e7267ea7fc969ee
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