diff --git a/docs/source/conf.py b/docs/source/conf.py
index 8d4b6b6db..3414fc7db 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -21,6 +21,29 @@ project = "PhotonVision"
 copyright = "2024, PhotonVision"
 author = "Banks Troutman, Matt Morley"
 
+# -- Git configuration -----------------------------------------------------
+import subprocess
+
+try:
+    # Use closest tag
+    git_tag_ref = (
+        subprocess.check_output(
+            [
+                "git",
+                "describe",
+                "--tags",
+            ],
+            stderr=subprocess.DEVNULL,
+        )
+        .strip()
+        .decode()
+    )
+except subprocess.CalledProcessError:
+    # Couldn't find closest tag, fallback to main
+    git_tag_ref = "main"
+
+myst_substitutions = {"git_tag_ref": git_tag_ref}
+
 # -- General configuration ---------------------------------------------------
 
 # Add any Sphinx extension module names here, as strings. They can be
@@ -158,4 +181,4 @@ if token:
     linkcheck_auth = [(R"https://github.com/.+", token)]
 
 # MyST configuration (https://myst-parser.readthedocs.io/en/latest/configuration.html)
-myst_enable_extensions = ["colon_fence"]
+myst_enable_extensions = ["colon_fence", "substitution"]
diff --git a/docs/source/docs/objectDetection/opi.md b/docs/source/docs/objectDetection/opi.md
index 210a9a7f2..52ae2fd91 100644
--- a/docs/source/docs/objectDetection/opi.md
+++ b/docs/source/docs/objectDetection/opi.md
@@ -14,6 +14,6 @@ PhotonVision currently ONLY supports 640x640 Ultralytics YOLOv5, YOLOv8, and YOL
 Only quantized models are supported, so take care when exporting to select the option for quantization.
 :::
 
-PhotonVision now ships with a [Python Notebook](https://github.com/PhotonVision/photonvision/blob/main/scripts/rknn-convert-tool/rknn_conversion.ipynb) that you can use in [Google Colab](https://colab.research.google.com) or in a local environment. In Google Colab, you can simply paste the PhotonVision GitHub URL into the "GitHub" tab and select the `rknn_conversion.ipynb` notebook without needing to manually download anything.
+PhotonVision now ships with a {{ '[Python Notebook](https://github.com/PhotonVision/photonvision/blob/{}/scripts/rknn-convert-tool/rknn_conversion.ipynb)'.format(git_tag_ref) }} that you can use in [Google Colab](https://colab.research.google.com) or in a local environment. In Google Colab, you can simply paste the PhotonVision GitHub URL into the "GitHub" tab and select the `rknn_conversion.ipynb` notebook without needing to manually download anything.
 
 Please ensure that the model you are attempting to convert is among the {ref}`supported models <docs/objectDetection/opi:Supported Models>` and using the PyTorch format.
diff --git a/docs/source/docs/objectDetection/rubik.md b/docs/source/docs/objectDetection/rubik.md
index 6f458e876..8976cbc23 100644
--- a/docs/source/docs/objectDetection/rubik.md
+++ b/docs/source/docs/objectDetection/rubik.md
@@ -14,7 +14,7 @@ PhotonVision currently ONLY supports 640x640 Ultralytics YOLOv8 and YOLOv11 mode
 Only quantized models are supported, so take care when exporting to select the option for quantization.
 :::
 
-PhotonVision now ships with a [Python Notebook](https://github.com/PhotonVision/photonvision/blob/main/scripts/rubik_conversion.ipynb) that you can use in [Google Colab](https://colab.research.google.com) or in a local environment. In Google Colab, you can simply paste the PhotonVision GitHub URL into the "GitHub" tab and select the `rubik_conversion.ipynb` notebook without needing to manually download anything.
+PhotonVision now ships with a {{ '[Python Notebook](https://github.com/PhotonVision/photonvision/blob/{}/scripts/rubik_conversion.ipynb)'.format(git_tag_ref) }} that you can use in [Google Colab](https://colab.research.google.com) or in a local environment. In Google Colab, you can simply paste the PhotonVision GitHub URL into the "GitHub" tab and select the `rubik_conversion.ipynb` notebook without needing to manually download anything.
 
 Please ensure that the model you are attempting to convert is among the {ref}`supported models <docs/objectDetection/rubik:Supported Models>` and using the PyTorch format.