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README.md

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+---
+license: mit
+tags:
+- image-classification
+- ai-detection
+- cnn
+- pytorch
+---
+
+# AI Detection CNN Model
+
+This model detects AI-generated images using spatial features extracted from Qwen2.5-VL.
+
+## Model Description
+
+- **Architecture**: 1D CNN with 3 convolutional layers
+- **Task**: Binary classification (AI-generated vs Real images)
+- **Feature Extractor**: Qwen2.5-VL-3B-Instruct
+- **Framework**: PyTorch
+
+## Usage
+
+```python
+from inference import test_image
+
+# Test an image
+result = test_image(
+    "path/to/image.jpg",
+    hf_repo_id="nahid112376/ai-detection-cnn",
+    threshold=0.5
+)
+
+print(f"Label: {result['label']}")
+print(f"Confidence: {result['confidence']*100:.2f}%")
+```
+
+## Model Details
+
+- Input: Spatial features from Qwen2.5-VL (shape: [num_patches, hidden_dim])
+- Output: Single regression score (0-1, threshold at 0.5)
+- Training: Trained on demectai dataset
+
+## Installation
+
+```bash
+pip install torch transformers huggingface_hub pillow numpy
+pip install qwen-vl-utils
+```
+
+## Files
+
+- `cnn_regression_model.pth`: Trained model weights
+- `inference.py`: Inference script
+- `extract_features.py`: Feature extraction script
+
+## Citation
+
+If you use this model, please cite:
+
+```bibtex
+@misc{ai-detection-cnn,
+  author = {bartazable},
+  title = {AI Detection CNN Model},
+  year = {2026},
+  publisher = {Hugging Face},
+  howpublished = {\url{https://huggingface.co/nahid112376/ai-detection-cnn}}
+}
+```