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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6bdd75dbe3330b7033d26ffb17bc659ed7e29abbf08fe624b61c018104de0901
- Size of remote file:
- 4.41 kB
- SHA256:
- 7127130e5d781b7792e2ace85631e70aa9562b8622e9997b73b1f5021b0d82e0
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