Update README.md

README.md

@@ -2,173 +2,156 @@
 license: mit
 pipeline_tag: text-to-image
 ---
-<div style="background: linear-gradient(135deg, #252525, #1a1a1a); padding: 2rem; border-radius: 12px; text-align: center; box-shadow: 0 4px 6px rgba(0,0,0,0.3); margin-bottom: 20px;">
-  <h1 style="color: #33b0d8; margin-bottom: 0.5rem; font-size: 2.5rem;">
-    PixelModel 🖼️
-  </h1>
-  <p style="color: #cccccc; font-size: 1.1rem; margin-top: 0;">
-    A neural network where the weights <strong>are</strong> the image.
-  </p>
-</div>
-
-<div style="background-color: #252525; padding: 1.5rem; border-radius: 12px; margin-bottom: 20px;">
-  <h2 style="color: #ffffff; margin-top: 0;">🧪 Dataset vs Outputs</h2>
-  <p style="color:#cccccc;">
-    Ground truth dataset images compared with generated outputs.
-  </p>
-
-  <table style="width: 100%; border-collapse: collapse; color: #cccccc; text-align: center;">
-    <tr>
-      <th style="padding: 10px; color:#33b0d8;">Red</th>
-      <th style="padding: 10px; color:#33b0d8;">Green</th>
-      <th style="padding: 10px; color:#33b0d8;">Blue</th>
-    </tr>
-    <tr>
-      <td style="padding: 10px;">
-        <div style="font-size: 0.8rem; color:#888;">dataset</div>
-        <img src="dataset/red.png" style="width: 110px; image-rendering: pixelated; border-radius: 6px;" />
-        <div style="font-size: 0.8rem; color:#888;">Model output</div>
-        <img src="out_red.png" style="width: 110px; image-rendering: pixelated; border-radius: 6px;" />
-      </td>
-      <td style="padding: 10px;">
-        <div style="font-size: 0.8rem; color:#888;">dataset</div>
-        <img src="dataset/green.png" style="width: 110px; image-rendering: pixelated; border-radius: 6px;" />
-        <div style="font-size: 0.8rem; color:#888;">Model output</div>
-        <img src="out_green.png" style="width: 110px; image-rendering: pixelated; border-radius: 6px;" />
-      </td>
-      <td style="padding: 10px;">
-        <div style="font-size: 0.8rem; color:#888;">dataset</div>
-        <img src="dataset/blue.png" style="width: 110px; image-rendering: pixelated; border-radius: 6px;" />
-        <div style="font-size: 0.8rem; color:#888;">Model output</div>
-        <img src="out_blue.png" style="width: 110px; image-rendering: pixelated; border-radius: 6px;" />
-      </td>
-    </tr>
-    <tr>
-      <th style="padding: 10px; color:#33b0d8;">White</th>
-      <th style="padding: 10px; color:#33b0d8;">Yellow</th>
-      <th style="padding: 10px; color:#33b0d8;">Dark</th>
-    </tr>
-    <tr>
-      <td style="padding: 10px;">
-        <div style="font-size: 0.8rem; color:#888;">dataset</div>
-        <img src="dataset/white.png" style="width: 110px; image-rendering: pixelated; border-radius: 6px;" />
-        <div style="font-size: 0.8rem; color:#888;">Model output</div>
-        <img src="out_white.png" style="width: 110px; image-rendering: pixelated; border-radius: 6px;" />
-      </td>
-      <td style="padding: 10px;">
-        <div style="font-size: 0.8rem; color:#888;">dataset</div>
-        <img src="dataset/yellow.png" style="width: 110px; image-rendering: pixelated; border-radius: 6px;" />
-        <div style="font-size: 0.8rem; color:#888;">Model output</div>
-        <img src="out_yellow.png" style="width: 110px; image-rendering: pixelated; border-radius: 6px;" />
-      </td>
-      <td style="padding: 10px;">
-        <div style="font-size: 0.8rem; color:#888;">dataset</div>
-        <img src="dataset/dark.png" style="width: 110px; image-rendering: pixelated; border-radius: 6px;" />
-        <div style="font-size: 0.8rem; color:#888;">Model output</div>
-        <img src="out_dark.png" style="width: 110px; image-rendering: pixelated; border-radius: 6px;" />
-      </td>
-    </tr>
-
-  </table>
-</div>
-
-<div style="background-color: #252525; padding: 1.5rem; border-radius: 12px; margin-bottom: 20px;">
-  <h2 style="color: #ffffff; margin-top: 0;">What is this?</h2>
-  <p style="color: #cccccc;">
-    <code>model.png</code> is not a picture of anything. It <em>is</em> the model.
-    Every pixel’s RGB values encode neural network weights:
-  </p>
-
-  <ul style="color: #cccccc; line-height: 1.6;">
-    <li><strong>R channel</strong> Model output weight magnitude</li>
-    <li><strong>B channel</strong> Model output weight sign (≥128 = positive)</li>
-    <li><strong>G channel</strong> Model output bias values</li>
-  </ul>
-
-  <p style="color: #cccccc;">
-    At inference time, pixels are parsed into 3 weight matrices (a tiny MLP).  
-    The prompt is embedded into a vector, then a forward pass generates a 32×32 image.
-  </p>
-
-  <p style="color: #cccccc;">
-    Training directly optimizes pixel values via gradient descent until the PNG itself becomes the model.
-  </p>
-</div>
-
-<div style="background-color: #252525; padding: 1.5rem; border-radius: 12px; margin-bottom: 20px;">
-  <h2 style="color: #ffffff; margin-top: 0;">📁 Files</h2>
-
-  <pre style="background:#1a1a1a; padding: 1rem; border-radius: 8px; color:#cccccc; overflow-x:auto;">
-model.png       ← THE MODEL (64×3200 px, ~284 KB)
+<div style="font-family: system-ui, sans-serif; background: #0f0f0f; color: #eaeaea; padding: 2rem; border-radius: 16px; max-width: 860px; margin: auto;">
+
+  <!-- HERO -->
+  <div style="background: #161616; border: 1px solid #222; padding: 2rem; border-radius: 14px; text-align: center; margin-bottom: 1.5rem;">
+    <h1 style="color: #33b0d8; font-size: 2rem; margin: 0 0 0.5rem;">PixelModel 🖼️</h1>
+    <p style="color: #aaa; font-size: 0.95rem; margin: 0;">
+      A neural network where the weights <strong style="color: #ddd;">are</strong> the image.
+    </p>
+  </div>
+
+  <!-- DATASET VS OUTPUTS -->
+  <div style="background: #161616; border: 1px solid #222; padding: 1.4rem; border-radius: 12px; margin-bottom: 1.5rem;">
+    <h2 style="color: #fff; font-size: 1rem; margin: 0 0 0.5rem;">🧪 Dataset vs Outputs</h2>
+    <p style="color: #aaa; font-size: 0.875rem; margin: 0 0 1rem;">Ground truth dataset images compared with generated outputs.</p>
+    <table style="width: 100%; border-collapse: collapse; text-align: center;">
+      <tr>
+        <th style="padding: 8px; color: #33b0d8; font-size: 0.85rem;">Red</th>
+        <th style="padding: 8px; color: #33b0d8; font-size: 0.85rem;">Green</th>
+        <th style="padding: 8px; color: #33b0d8; font-size: 0.85rem;">Blue</th>
+      </tr>
+      <tr>
+        <td style="padding: 8px;">
+          <div style="font-size: 0.75rem; color: #555; margin-bottom: 4px;">dataset</div>
+          <img src="dataset/red.png" style="width: 100px; image-rendering: pixelated; border-radius: 6px; display: block; margin: auto;" />
+          <div style="font-size: 0.75rem; color: #555; margin: 4px 0;">output</div>
+          <img src="out_red.png" style="width: 100px; image-rendering: pixelated; border-radius: 6px; display: block; margin: auto;" />
+        </td>
+        <td style="padding: 8px;">
+          <div style="font-size: 0.75rem; color: #555; margin-bottom: 4px;">dataset</div>
+          <img src="dataset/green.png" style="width: 100px; image-rendering: pixelated; border-radius: 6px; display: block; margin: auto;" />
+          <div style="font-size: 0.75rem; color: #555; margin: 4px 0;">output</div>
+          <img src="out_green.png" style="width: 100px; image-rendering: pixelated; border-radius: 6px; display: block; margin: auto;" />
+        </td>
+        <td style="padding: 8px;">
+          <div style="font-size: 0.75rem; color: #555; margin-bottom: 4px;">dataset</div>
+          <img src="dataset/blue.png" style="width: 100px; image-rendering: pixelated; border-radius: 6px; display: block; margin: auto;" />
+          <div style="font-size: 0.75rem; color: #555; margin: 4px 0;">output</div>
+          <img src="out_blue.png" style="width: 100px; image-rendering: pixelated; border-radius: 6px; display: block; margin: auto;" />
+        </td>
+      </tr>
+      <tr>
+        <th style="padding: 8px; color: #33b0d8; font-size: 0.85rem;">White</th>
+        <th style="padding: 8px; color: #33b0d8; font-size: 0.85rem;">Yellow</th>
+        <th style="padding: 8px; color: #33b0d8; font-size: 0.85rem;">Dark</th>
+      </tr>
+      <tr>
+        <td style="padding: 8px;">
+          <div style="font-size: 0.75rem; color: #555; margin-bottom: 4px;">dataset</div>
+          <img src="dataset/white.png" style="width: 100px; image-rendering: pixelated; border-radius: 6px; display: block; margin: auto;" />
+          <div style="font-size: 0.75rem; color: #555; margin: 4px 0;">output</div>
+          <img src="out_white.png" style="width: 100px; image-rendering: pixelated; border-radius: 6px; display: block; margin: auto;" />
+        </td>
+        <td style="padding: 8px;">
+          <div style="font-size: 0.75rem; color: #555; margin-bottom: 4px;">dataset</div>
+          <img src="dataset/yellow.png" style="width: 100px; image-rendering: pixelated; border-radius: 6px; display: block; margin: auto;" />
+          <div style="font-size: 0.75rem; color: #555; margin: 4px 0;">output</div>
+          <img src="out_yellow.png" style="width: 100px; image-rendering: pixelated; border-radius: 6px; display: block; margin: auto;" />
+        </td>
+        <td style="padding: 8px;">
+          <div style="font-size: 0.75rem; color: #555; margin-bottom: 4px;">dataset</div>
+          <img src="dataset/dark.png" style="width: 100px; image-rendering: pixelated; border-radius: 6px; display: block; margin: auto;" />
+          <div style="font-size: 0.75rem; color: #555; margin: 4px 0;">output</div>
+          <img src="out_dark.png" style="width: 100px; image-rendering: pixelated; border-radius: 6px; display: block; margin: auto;" />
+        </td>
+      </tr>
+    </table>
+  </div>
+
+  <!-- WHAT IS THIS -->
+  <div style="background: #161616; border: 1px solid #222; padding: 1.4rem; border-radius: 12px; margin-bottom: 1.5rem;">
+    <h2 style="color: #fff; font-size: 1rem; margin: 0 0 0.6rem;">What is this?</h2>
+    <p style="color: #aaa; font-size: 0.875rem; line-height: 1.7; margin: 0 0 0.75rem;">
+      <code style="background: #1e1e1e; padding: 2px 6px; border-radius: 4px;">model.png</code> is not a picture of anything — it <em>is</em> the model.
+      Every pixel's RGB values encode neural network weights:
+    </p>
+    <ul style="color: #aaa; font-size: 0.875rem; line-height: 1.7; margin: 0 0 0.75rem; padding-left: 1.1rem;">
+      <li><strong style="color: #ddd;">R channel</strong> — weight magnitude</li>
+      <li><strong style="color: #ddd;">B channel</strong> — weight sign (≥128 = positive)</li>
+      <li><strong style="color: #ddd;">G channel</strong> — bias values</li>
+    </ul>
+    <p style="color: #aaa; font-size: 0.875rem; line-height: 1.7; margin: 0;">
+      At inference, pixels are parsed into 3 weight matrices forming a tiny MLP.
+      The prompt is embedded into a vector, then a forward pass generates a 32×32 image.
+      Training directly optimizes pixel values via gradient descent until the PNG itself becomes the model.
+    </p>
+  </div>
+
+  <!-- FILES -->
+  <div style="background: #161616; border: 1px solid #222; padding: 1.4rem; border-radius: 12px; margin-bottom: 1.5rem;">
+    <h2 style="color: #fff; font-size: 1rem; margin: 0 0 0.75rem;">📁 Files</h2>
+    <pre style="background: #111; border: 1px solid #1e1e1e; padding: 1rem; border-radius: 8px; color: #aaa; font-size: 0.8rem; overflow-x: auto; margin: 0;">
+model.png       ← THE MODEL (64×3200 px)
 main.py         ← inference
 train.py        ← training
-model.py        ← architecture (pixels Model output weights Model output forward pass)
+model.py        ← architecture
 dataset/        ← training data
   cat.png
   cat.txt       ← prompt: "a cat"
-...
-  </pre>
-</div>
-
-<div style="background-color: #252525; padding: 1.5rem; border-radius: 12px; margin-bottom: 20px;">
-  <h2 style="color: #ffffff; margin-top: 0;">⚙️ Usage</h2>
-
-  <h3 style="color:#33b0d8;">Train</h3>
-  <pre style="background:#1a1a1a; padding: 1rem; border-radius: 8px; color:#cccccc;">
+  ...</pre>
+  </div>
+
+  <!-- USAGE -->
+  <div style="background: #161616; border: 1px solid #222; padding: 1.4rem; border-radius: 12px; margin-bottom: 1.5rem;">
+    <h2 style="color: #fff; font-size: 1rem; margin: 0 0 0.75rem;">⚙️ Usage</h2>
+    <p style="color: #33b0d8; font-size: 0.8rem; font-weight: 600; margin: 0 0 0.3rem;">Train</p>
+    <pre style="background: #111; border: 1px solid #1e1e1e; padding: 0.9rem; border-radius: 8px; color: #aaa; font-size: 0.8rem; margin: 0 0 1rem;">
 python train.py
-python train.py --epochs 500 --lr 0.05
-  </pre>
-
-  <h3 style="color:#33b0d8;">Generate</h3>
-  <pre style="background:#1a1a1a; padding: 1rem; border-radius: 8px; color:#cccccc;">
+python train.py --epochs 500 --lr 0.05</pre>
+    <p style="color: #33b0d8; font-size: 0.8rem; font-weight: 600; margin: 0 0 0.3rem;">Generate</p>
+    <pre style="background: #111; border: 1px solid #1e1e1e; padding: 0.9rem; border-radius: 8px; color: #aaa; font-size: 0.8rem; margin: 0 0 0.75rem;">
 python main.py "red"
-python main.py "a cat" --out cat_out.png --scale 8
-  </pre>
-
-  <p style="color:#cccccc;">
-    <code>--scale 8</code> upscales 32×32 Model output 256×256 using nearest-neighbour interpolation to preserve pixel structure.
-  </p>
-</div>
-
-<div style="background-color: #252525; padding: 1.5rem; border-radius: 12px; margin-bottom: 20px;">
-  <h2 style="color: #ffffff; margin-top: 0;">🧠 Architecture</h2>
-
-  <pre style="background:#1a1a1a; padding: 1rem; border-radius: 8px; color:#cccccc;">
+python main.py "a cat" --out cat_out.png --scale 8</pre>
+    <p style="color: #aaa; font-size: 0.8rem; margin: 0;">
+      <code style="background: #1e1e1e; padding: 2px 6px; border-radius: 4px;">--scale 8</code> upscales 32×32 → 256×256 using nearest-neighbour interpolation.
+    </p>
+  </div>
+
+  <!-- ARCHITECTURE -->
+  <div style="background: #161616; border: 1px solid #222; padding: 1.4rem; border-radius: 12px; margin-bottom: 1.5rem;">
+    <h2 style="color: #fff; font-size: 1rem; margin: 0 0 0.75rem;">🧠 Architecture</h2>
+    <pre style="background: #111; border: 1px solid #1e1e1e; padding: 1rem; border-radius: 8px; color: #aaa; font-size: 0.8rem; overflow-x: auto; margin: 0 0 0.75rem;">
 prompt string
-  Model output char-level embedding Model output 32-dim vector
-  Model output W1 (64×32) Model output tanh
-  Model output W2 (64×64) Model output tanh  
-  Model output W3 (3072×64) Model output sigmoid
-  Model output reshape Model output 32×32×3 image
-  </pre>
-
-  <p style="color:#cccccc;">
-    All weights live inside <code>model.png</code>. Opening the PNG is literally opening the neural network.
-  </p>
-</div>
-
-<div style="background-color: #252525; padding: 1.5rem; border-radius: 12px; margin-bottom: 20px;">
-  <h2 style="color: #ffffff; margin-top: 0;">📊 Dataset Tips</h2>
-
-  <ul style="color:#cccccc; line-height:1.6;">
-    <li>6–20 image-prompt pairs is enough</li>
-    <li>Simple targets converge fastest (solid colors, gradients, shapes)</li>
-    <li>200–500 epochs typically sufficient</li>
-    <li>Loss below 0.001 is good for simple datasets</li>
-    <li>Model capacity is fixed (~600K implicit parameters)</li>
-  </ul>
-</div>
-
-<div style="background: linear-gradient(135deg, #1f1f1f, #101010); padding: 2rem; border-radius: 12px; text-align: center; box-shadow: 0 4px 6px rgba(0,0,0,0.4);">
-  <h2 style="color: #ffffff;">Why?</h2>
-  <p style="color: #cccccc;">
-    It’s a toy. It’s not useful. But it’s cool that it works.
-  </p>
-</div>
+  → char-level embedding → 32-dim vector
+  → W1 (64×32)  → tanh
+  → W2 (64×64)  → tanh
+  → W3 (3072×64) → sigmoid
+  → reshape → 32×32×3 image</pre>
+    <p style="color: #aaa; font-size: 0.875rem; margin: 0;">
+      All weights live inside <code style="background: #1e1e1e; padding: 2px 6px; border-radius: 4px;">model.png</code>. Opening the PNG is literally opening the neural network.
+    </p>
+  </div>
+
+  <!-- DATASET TIPS -->
+  <div style="background: #161616; border: 1px solid #222; padding: 1.4rem; border-radius: 12px; margin-bottom: 1.5rem;">
+    <h2 style="color: #fff; font-size: 1rem; margin: 0 0 0.6rem;">📊 Dataset Tips</h2>
+    <ul style="color: #aaa; font-size: 0.875rem; line-height: 1.7; margin: 0; padding-left: 1.1rem;">
+      <li>6–20 image-prompt pairs is enough</li>
+      <li>Simple targets converge fastest (solid colors, gradients, shapes)</li>
+      <li>200–500 epochs typically sufficient</li>
+      <li>Loss below 0.001 is good for simple datasets</li>
+      <li>Model capacity is fixed (~600K implicit parameters)</li>
+    </ul>
+  </div>
+
+  <!-- FOOTER -->
+  <div style="background: #161616; border: 1px solid #222; padding: 1.2rem; border-radius: 12px; text-align: center;">
+    <p style="color: #aaa; font-size: 0.875rem; margin: 0 0 0.25rem;">
+      It's a toy. It's not useful. But it's cool that it works.
+    </p>
+    <p style="color: #444; font-size: 0.8rem; margin: 0;">Seton Labs · Coordinate · Evaluate · Upgrade</p>
+  </div>
 
-<div style="background: linear-gradient(135deg, #1f1f1f, #101010); padding: 2rem; border-radius: 12px; text-align: center; margin-top: 20px;">
-  <h2 style="color: #ffffff;">Seton Labs</h2>
-  <p style="color: #cccccc;">
-    Coordinate, evaluate, upgrade 
-  </p>
 </div>