Update README.md

README.md

@@ -211,35 +211,11 @@ license: apache-2.0
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-          <td><code>north-code-quant-Q8_0.gguf</code></td>
+          <td><code>North-Code-Quant.gguf</code></td>
           <td><span class="nc-quant-tag">Q8_0</span></td>
           <td>-- GB</td>
           <td>Near-lossless. Best quality, higher VRAM/RAM requirement.</td>
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-        <tr>
-          <td><code>north-code-quant-Q6_K.gguf</code></td>
-          <td><span class="nc-quant-tag">Q6_K</span></td>
-          <td>-- GB</td>
-          <td>Very low perplexity loss. Great for critical code tasks.</td>
-        </tr>
-        <tr style="background: rgba(88, 166, 255, 0.05);">
-          <td><code>north-code-quant-Q4_K_M.gguf</code></td>
-          <td><span class="nc-quant-tag">Q4_K_M</span></td>
-          <td>-- GB</td>
-          <td><strong>⭐ Recommended.</strong> Best size/performance ratio.</td>
-        </tr>
-        <tr>
-          <td><code>north-code-quant-Q3_K_M.gguf</code></td>
-          <td><span class="nc-quant-tag">Q3_K_M</span></td>
-          <td>-- GB</td>
-          <td>Lower resource usage. Noticeable quality degradation in complex reasoning.</td>
-        </tr>
-        <tr>
-          <td><code>north-code-quant-IQ4_XS.gguf</code></td>
-          <td><span class="nc-quant-tag">IQ4_XS</span></td>
-          <td>-- GB</td>
-          <td>Importance Matrix quant. Smaller than Q4 with similar quality.</td>
-        </tr>
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@@ -251,11 +227,6 @@ license: apache-2.0
     <a href="https://huggingface.co/CohereForAI/c4ai-command-r-plus" target="_blank">Cohere North Code</a> 
     weights using <code>llama.cpp</code> with importance matrix calibration for optimal token-level precision retention.
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-  <ul style="color: var(--nc-text-muted); padding-left: 1.5rem;">
-    <li><strong>Calibration Dataset:</strong> CodeAlpaca + SlimOrca subset</li>
-    <li><strong>Imatrix:</strong> Enabled for K-quants (Q3_K through Q6_K)</li>
-    <li><strong>Vocab:</strong> Original Cohere tokenizer preserved</li>
-  </ul>
 
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