Instructions to use Modotte/AIRealNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Modotte/AIRealNet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Modotte/AIRealNet") 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("Modotte/AIRealNet") model = AutoModelForImageClassification.from_pretrained("Modotte/AIRealNet", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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- [GitHub Repository](https://github.com/XenArcAI/AIRealNet)
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## Overview
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In an era of rapidly advancing AI-generated imagery, deepfakes, and synthetic media, the need for reliable detection tools has never been higher. **AIRealNet** is a binary image classifier explicitly designed to distinguish **AI-generated images** from **real human photographs**. This model is optimized to detect conventional AI-generated content while adhering to strict privacy standards—avoiding personal or sensitive images.
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- [GitHub Repository](https://github.com/XenArcAI/AIRealNet)
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- [Live Demo](https://huggingface.co/spaces/Parveshiiii/AIRealNet)
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## Overview
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In an era of rapidly advancing AI-generated imagery, deepfakes, and synthetic media, the need for reliable detection tools has never been higher. **AIRealNet** is a binary image classifier explicitly designed to distinguish **AI-generated images** from **real human photographs**. This model is optimized to detect conventional AI-generated content while adhering to strict privacy standards—avoiding personal or sensitive images.
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