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@@ -779,12 +779,14 @@ <h3 id="using-pip">Using pip<a class="headerlink" href="#using-pip" title="Perma
 <div class="highlight"><pre><span></span><code><span class="linenos" data-linenos="1 "></span>pip<span class="w"> </span>install<span class="w"> </span>pyg_lib<span class="w"> </span>torch_scatter<span class="w"> </span>torch_sparse<span class="w"> </span>torch_cluster<span class="w"> </span>torch_spline_conv<span class="w"> </span>-f<span class="w"> </span>https://data.pyg.org/whl/torch-<span class="si">${</span><span class="nv">TORCH</span><span class="si">}</span>+<span class="si">${</span><span class="nv">CUDA</span><span class="si">}</span>.html
 </code></pre></div></p>
 <hr/>
-<p>where <code>${TORCH}</code> and <code>${CUDA}</code> should be replaced by the specific PyTorch and CUDA versions, respectively:
- 1.  PyTorch 2.3: <code>${TORCH}=2.3.0</code> and <code>${CUDA}=cpu|cu118|cu121</code>
- 2.  PyTorch 2.2: <code>${TORCH}=2.2.0</code> and <code>${CUDA}=cpu|cu118|cu121</code>
- 3.  PyTorch 2.1: <code>${TORCH}=2.1.0</code> and <code>${CUDA}=cpu|cu118|cu121</code>
- 4.  PyTorch 2.0: <code>${TORCH}=2.0.0</code> and <code>${CUDA}=cpu|cu117|cu118</code>
- 5.  PyTorch 1.13: <code>${TORCH}=1.13.0</code> and ${CUDA}=cpu|cu116|cu117`</p>
+<p>where <code>${TORCH}</code> and <code>${CUDA}</code> should be replaced by the specific PyTorch and CUDA versions, respectively:</p>
+<p><ul>
+<li>PyTorch 2.3: <code><span class="arithmatex" cuda="CUDA">\({TORCH}=2.3.0&lt;/code&gt; and &lt;code&gt;\)</span>=cpu|cu118|cu121</code></li>
+<li>PyTorch 2.2: <code><span class="arithmatex" cuda="CUDA">\({TORCH}=2.2.0&lt;/code&gt; and &lt;code&gt;\)</span>=cpu|cu118|cu121</code></li>
+<li>PyTorch 2.1: <code><span class="arithmatex" cuda="CUDA">\({TORCH}=2.1.0&lt;/code&gt; and &lt;code&gt;\)</span>=cpu|cu118|cu121</code></li>
+<li>PyTorch 2.0: <code><span class="arithmatex" cuda="CUDA">\({TORCH}=2.0.0&lt;/code&gt; and &lt;code&gt;\)</span>=cpu|cu117|cu118</code></li>
+<li>PyTorch 1.13: <code><span class="arithmatex" cuda="CUDA">\({TORCH}=1.13.0&lt;/code&gt; and &lt;code&gt;\)</span>=cpu|cu116|cu117</code></li>
+</ul></p>
 <hr/>
 <p>For example, for PyTorch 2.3.* and CUDA 12.1, type:</p>
 <div class="highlight"><pre><span></span><code><span class="linenos" data-linenos="1 "></span>pip<span class="w"> </span>install<span class="w"> </span>pyg_lib<span class="w"> </span>torch_scatter<span class="w"> </span>torch_sparse<span class="w"> </span>torch_cluster<span class="w"> </span>torch_spline_conv<span class="w"> </span>-f<span class="w"> </span>https://data.pyg.org/whl/torch-2.3.0+cu121.html