Fixed internal links

Signed-off-by: Eliot Heinrich <eheinrich@nvidia.com>

Author: eliotheinrich

docs/sphinx/api/qec/tensor_network_decoder_api.rst

@@ -13,7 +13,7 @@
     decoder. Use `pip install cudaq-qec[tensor-network-decoder]` in order to use
     this decoder.
 
-    The Tensor Network Decoder has the same GPU support as the `Quantum Low-Density Parity-Check Decoder <https://nvidia.github.io/cudaqx/components/qec/decoders.html#quantum-low-density-parity-check-decoder>`__.
+    The Tensor Network Decoder has the same GPU support as the :ref:`Quantum Low-Density Parity-Check Decoder <qldpc_decoder>`.
     However, if you are using the V100 GPU (SM70), you will need to pin your
     cuTensor version to 2.2 by running `pip install cutensor_cu12==2.2`. Note
     that this GPU is not supported by the Tensor Network Decoder.

docs/sphinx/components/qec/decoders.rst

@@ -268,6 +268,8 @@ In Python, the ``backend`` parameter (``"auto"``, ``"gpu"``, or ``"cpu"``) contr
 For a complete, runnable walkthrough — including GPU acceleration and input-type handling — see the :ref:`DEM Sampling example <dem_sampling_example>`.
 
 
+.. _prebuilt_qec_decoders:
+
 Pre-built QEC Decoders
 ----------------------
 
@@ -332,6 +334,8 @@ CUDA-Q QEC provides pre-built decoders for a variety of use cases.
 
 Here's a detailed overview of each:
 
+.. _qldpc_decoder:
+
 Quantum Low-Density Parity-Check Decoder
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
@@ -471,7 +475,7 @@ The decoder returns the probability that the logical observable has flipped for
 .. note::
 
     In general, the Tensor Network Decoder has the same GPU support as the
-    `Quantum Low-Density Parity-Check Decoder <https://nvidia.github.io/cudaqx/components/qec/decoders.html#quantum-low-density-parity-check-decoder>`__.
+    :ref:`Quantum Low-Density Parity-Check Decoder <qldpc_decoder>`.
     However, if you are using the V100 GPU (SM70), you will need to pin your
     cuTensor version to 2.2 by running `pip install cutensor_cu12==2.2`. Note
     that this GPU will not be supported by the Tensor Network Decoder when

docs/sphinx/examples_rst/qec/getting_started_realtime_decoding.rst

@@ -625,7 +625,7 @@ They are valid both for python and C++ applications, however, they must be set b
 
 Decoder Selection
 ^^^^^^^^^^^^^^^^^
-The page `CUDA-Q QEC Decoders <https://nvidia.github.io/cudaqx/components/qec/decoders.html#pre-built-qec-decoders>`_ provides information about which decoders are compatible with realtime decoding.
+The :ref:`Pre-built QEC Decoders <prebuilt_qec_decoders>` section provides information about which decoders are compatible with realtime decoding.
 
 The TRT decoder (``trt_decoder``) can be configured for realtime decoding by specifying
 its ``decoder_custom_args`` parameters. This is useful for neural network-based