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Imager-1 is an AI model designed to detect AI-generated images with high precision; it can detect DALL-E 2. We will soon launch imager-1-small and imager-2, which will be able to detect DALL-E 3 and other text-to-image models.
| 🎯 Accuracy | 📉 Loss | 🧠 Parameters |
|---|---|---|
| 98.18% | 0.1717 | 50M |
Validation Accuracy: 98.18% — evaluated on 15% of the dataset, never seen during training.
Validation Loss: 0.1717 — the model shows strong generalization with no signs of overfitting.
Parameters: 50M — optimized for real-world deployment, including browser inference via ONNX.
This repository contains the base model of Imager-1, released for developers and researchers who want direct access to the architecture, weights, and training pipeline.
Imager always publishes a separately verified and production-ready version of each model, tested against real-world generators before release. This base model is provided so the community can build on top of it, fine-tune it, or integrate it into their own systems.
Access to the most powerful Imager models is always granted through the official channels.
Binary image classification.
| Label | Meaning |
|---|---|
0 |
AI-generated |
1 |
Real |
Apache 2.0