Update README.md

README.md

@@ -87,6 +87,8 @@ on ~20K real MS-COCO caption/image pairs.
 | Weight precision | 8-bit (G channel wasted) | **16-bit** (R=high byte, G=low byte) |
 | Training data | 6 solid-color swatches | ~20K MS-COCO caption/image pairs |
 
+<img src="pixelmodel-v1-loss.png" alt="Training loss curve crossing below both naive-predictor baselines" style="width: 100%; max-width: 720px;">
+
 ## 🎨 Weight Encoding
 
 Each pixel stores one weight at 16-bit precision, mapped from [-2, 2]:
@@ -151,6 +153,8 @@ objects. It learns caption-conditioned color, layout, and texture statistics of
 COCO photos — the outputs are blurry impressions, not pictures. The point is
 the size:quality ratio and the PNG-as-model gimmick, executed honestly.
 
+<img src="pixelmodel-v1-probe.png" alt="Target photos vs model outputs: the model produces caption-conditioned color washes" style="width: 100%; max-width: 640px;">
+
 ## ⚙️ Usage
 
 ```bash