voxel51 · brimoor · Mar 15, 2024 · Mar 7, 2024 · Mar 7, 2024 · Mar 7, 2024
diff --git a/docs/source/_static/images/tutorials/zero_shot_classification.png b/docs/source/_static/images/tutorials/zero_shot_classification.png
diff --git a/docs/source/tutorials/images/zero_shot_classification_all_wrong_view.png b/docs/source/tutorials/images/zero_shot_classification_all_wrong_view.png
diff --git a/docs/source/tutorials/images/zero_shot_classification_initial_dataset.png b/docs/source/tutorials/images/zero_shot_classification_initial_dataset.png
diff --git a/docs/source/tutorials/images/zero_shot_classification_install_plugin.gif b/docs/source/tutorials/images/zero_shot_classification_install_plugin.gif
diff --git a/docs/source/tutorials/images/zero_shot_classification_one_right_view.png b/docs/source/tutorials/images/zero_shot_classification_one_right_view.png
diff --git a/docs/source/tutorials/images/zero_shot_classification_run_plugin.gif b/docs/source/tutorials/images/zero_shot_classification_run_plugin.gif
diff --git a/docs/source/tutorials/images/zero_shot_classification_siglip_not_clip_view.gif b/docs/source/tutorials/images/zero_shot_classification_siglip_not_clip_view.gif
diff --git a/docs/source/tutorials/index.rst b/docs/source/tutorials/index.rst
@@ -145,6 +145,13 @@ your datasets and turn your good models into *great models*.
     :image: ../_static/images/tutorials/dimension_reduction.png
     :tags: Brain,Visualization
 
+.. customcarditem::
+    :header: Zero-Shot Image Classification
+    :description: Run and evaluate zero-shot image classification models with OpenCLIP, Hugging Face Transformers, and FiftyOne.
+    :link: zero_shot_classification.html
+    :image: ../_static/images/tutorials/zero_shot_classification.png
+    :tags: Filtering,Model-Evaluation,Model-Zoo
+
 .. customcarditem::
     :header: Augmenting Datasets with Albumentations
     :description: Learn how to apply and test out different augmentations on your datasets using FiftyOne and Albumentations.
@@ -192,4 +199,5 @@ your datasets and turn your good models into *great models*.
    3D point clouds with Point-E <pointe.ipynb>
    Monocular depth estimation <monocular_depth_estimation.ipynb>
    Dimensionality reduction <dimension_reduction.ipynb>
+   Zero-shot classification <zero_shot_classification.ipynb>
    Data augmentation <data_augmentation.ipynb>