Instructions to use dima806/ai_vs_real_image_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/ai_vs_real_image_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dima806/ai_vs_real_image_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("dima806/ai_vs_real_image_detection") model = AutoModelForImageClassification.from_pretrained("dima806/ai_vs_real_image_detection") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f53ad08419a355c7f5a725b33953fa2b61d0a36090f68a6426e088d139b297f3
- Size of remote file:
- 343 MB
- SHA256:
- c3ee9511c4aea31585701b13cc75639e26bb4437581af161244d4996fc509d57
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