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README.md

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-# AI Detection Meta-Classifier Weights
-
-Stacking meta-classifier weights for multi-modal AI content detection.
-
-## What's in this repo
-
-| File | Description |
-|------|-------------|
-| `config.json` | Full config with model IDs + meta-classifier weights |
-| `meta_classifier_weights.json` | Same weights (explicit name) |
-
-## Architecture
-
-Each modality uses **StandardScaler + LogisticRegression** on top of multiple neural model scores:
-
-| Modality | Neural Models | Meta-Classifier Features | Accuracy |
-|----------|--------------|-------------------------|----------|
-| **Image** | 4x ViT classifiers | 4 model scores + FFT slope + HF ratio (6 features) | **99.1%** |
-| **Audio** | 2x wav2vec2 classifiers | 2 model scores + 5 spectral features (7 features) | **82.0%** |
-| **Text** | Falcon-7B (Binoculars) + RoBERTa | 2 model scores + 5 statistical features (7 features) | **97.5%** |
-
-## Neural Network Models (hosted on their original HF repos)
-
-**Image:**
-- `NYUAD-ComNets/NYUAD_AI-generated_images_detector`
-- `Organika/sdxl-detector`
-- `umm-maybe/AI-image-detector`
-- `dima806/ai_vs_real_image_detection`
-
-**Audio:**
-- `DavidCombei/wav2vec2-xls-r-1b-DeepFake-AI4TRUST`
-- `Gustking/wav2vec2-large-xlsr-deepfake-audio-classification`
-
-**Text:**
-- `tiiuae/falcon-7b` + `tiiuae/falcon-7b-instruct` (Binoculars method)
-- `Hello-SimpleAI/chatgpt-detector-roberta`
-
-## Usage
-
-The weights in this repo are the **meta-classifier layer only** (scaler params + logistic regression coefficients).
-The large neural network weights are downloaded from their original HuggingFace repos at runtime.