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@@ -156,36 +156,6 @@ in this demonstration.  Multiple Bin numbers are also support</p>
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-<h2 id="use-nctookit-to-calibrate-your-own-models">Use NCTookit to Calibrate Your Own Models</h2>
-<p>Quick Start by running the following code! Or, <a href="https://colab.research.google.com/drive/1HosL29iJxK7Z8wNR9X3aWCgvbdu1ZgFu"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab" /></a>.
-Using this tool, users can use our proposed package, \(\texttt{NCTookit}\), to calibrate the model.</p>
-
-<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="c1"># !pip install -q git+https://github.com/yungchentang/NCToolkit.git
-</span><span class="kn">from</span> <span class="nn">neural_clamping.nc_wrapper</span> <span class="kn">import</span> <span class="n">NCWrapper</span>
-<span class="kn">from</span> <span class="nn">neural_clamping.utils</span> <span class="kn">import</span> <span class="n">load_model</span><span class="p">,</span> <span class="n">load_dataset</span><span class="p">,</span> <span class="n">model_classes</span><span class="p">,</span> <span class="n">plot_reliability_diagram</span>
-
-<span class="c1"># Load model
-</span><span class="n">model</span> <span class="o">=</span> <span class="n">load_model</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s">'ARCHITECTURE'</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="s">'DATASET'</span><span class="p">,</span> <span class="n">checkpoint_path</span><span class="o">=</span><span class="s">'CHECKPOINT_PATH'</span><span class="p">)</span>
-<span class="n">num_classes</span> <span class="o">=</span> <span class="n">model_classes</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s">'DATASET'</span><span class="p">)</span>
-
-<span class="c1"># Dataset loader
-</span><span class="n">valloader</span> <span class="o">=</span> <span class="n">load_dataset</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s">'DATASET'</span><span class="p">,</span> <span class="n">split</span><span class="o">=</span><span class="s">'val'</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="s">"BATCH_SIZE"</span><span class="p">)</span>
-<span class="n">testloader</span> <span class="o">=</span> <span class="n">load_dataset</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="s">'DATASET'</span><span class="p">,</span> <span class="n">split</span><span class="o">=</span><span class="s">'test'</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="s">"BATCH_SIZE"</span><span class="p">)</span>
-
-<span class="c1"># Build Neural Clamping framework
-</span><span class="n">nc</span> <span class="o">=</span> <span class="n">NCWrapper</span><span class="p">(</span><span class="n">model</span><span class="o">=</span><span class="n">model</span><span class="p">,</span> <span class="n">num_classes</span><span class="o">=</span><span class="n">num_classes</span><span class="p">,</span> <span class="p">...)</span>
-
-<span class="c1"># Calibrated using Neural Clamping
-</span><span class="n">nc</span><span class="p">.</span><span class="n">train_NC</span><span class="p">(</span><span class="n">val_loader</span><span class="o">=</span><span class="n">valloader</span><span class="p">,</span> <span class="n">epoch</span><span class="o">=</span><span class="s">'EPOCH'</span><span class="p">,</span> <span class="p">...)</span>
-
-<span class="c1"># General Evaluation
-</span><span class="n">nc</span><span class="p">.</span><span class="n">test_with_NC</span><span class="p">(</span><span class="n">test_loader</span><span class="o">=</span><span class="n">testloader</span><span class="p">)</span>
-
-<span class="c1"># Visualization
-</span><span class="n">bin_acc</span><span class="p">,</span> <span class="n">conf_axis</span><span class="p">,</span> <span class="n">ece_score</span> <span class="o">=</span> <span class="n">nc</span><span class="p">.</span><span class="n">reliability_diagram</span><span class="p">(</span><span class="n">test_loader</span><span class="o">=</span><span class="n">testloader</span><span class="p">,</span> <span class="n">rd_criterion</span><span class="o">=</span><span class="s">"ECE"</span><span class="p">,</span> <span class="n">n_bins</span><span class="o">=</span><span class="mi">30</span><span class="p">)</span>
-<span class="n">plot_reliability_diagram</span><span class="p">(</span><span class="n">conf_axis</span><span class="p">,</span> <span class="n">bin_acc</span><span class="p">)</span>
-</code></pre></div></div>
-
 <h2 id="citations">Citations</h2>
 <p>If you find Neural Clamping helpful and useful for your research, please cite our main paper as follows:</p>