Instructions to use Hemgg/AI-vs-Real-Image-Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hemgg/AI-vs-Real-Image-Detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Hemgg/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("Hemgg/AI-vs-Real-Image-Detection") model = AutoModelForImageClassification.from_pretrained("Hemgg/AI-vs-Real-Image-Detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a530de4bcb17a22f1e89c0192268c6ec2bd322e57510d7199d6bec78874d6539
- Size of remote file:
- 4.92 kB
- SHA256:
- d1465287bb4fd592088d896d7daeee28c30c66d3660acba9e33af51083cb4cf3
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