Update README.md

README.md

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-license: etalab-2.0
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+ ---
+
+license: etalab-2.0
+
+
+## 📦 Model Weights
+
+
+The trained weights for all benchmarks are hosted on Hugging Face.
+
+
+### 📂 Weights Organization
+
+Download the weights and place them in the `TiBuDB_trained_weights/` directory.
+
+
+| Task | Model | Weight File | Description | Sahi crop size | Inference size
+
+| :--- | :--- | :--- | :--- | :--- | :--- |
+
+| **Detection** | YOLO26x | `best_det_yolo26x_seed1000_baseline.pt` | Baseline (1x) | 128 | 128 |
+
+| **Detection** | YOLO26x | `best_det_yolo26x_seed1000_x4.pt` | Upscaled (4x) | 128 | 512 |
+
+| **Detection** | RF-DETR | `best_ema_det_rfdetr_large_seed0_baseline.pth` | Transformer Baseline | 128 (basesize) | N/A | 
+
+| **Segmentation**| YOLO26x | `best_seg_yolo26x_seed100_baseline.pt` | Baseline (1x) | 128 | 128 |
+
+| **Segmentation**| YOLO26x | `best_seg_yolo26x_seed100_x4.pt` | Upscaled (4x) | 128 | 512 |
+
+| **Segmentation**| RF-DETR | `best_ema_seg_rfdetr_large_seed100_baseline.pth` | Transformer Baseline | 128 (basesize) | N/A | 
+
+| **OBB** | YOLO26x | `best_obb_yolo26x_seed5000_baseline.pt` | Oriented Bbox (1x) | 128 | 512 |
+
+| **OBB** | YOLO26x | `best_obb_yolo26x_seed5000_x4.pt` | Oriented Bbox (4x) | 128 | 512 |
+
+
+### 🛠️ Quick Load Example (Ultralytics)
+
+```python
+
+from ultralytics import YOLO
+
+model = YOLO("TiBuDB_trained_weights/best_det_yolo26x_seed1000_baseline.pt")
+
+results = model.predict("data/tibudb_dataset/yolo_det/val/images/test_image.png")
+
+---