Update example url to hotfix/0.100.x

docs/advanced-usage/set-up-natural-language-search.md

@@ -11,9 +11,9 @@ Users may set up this functionality by extracting and uploading the correspondin
 ## Example
 
 The [`kolena`](https://github.com/kolenaIO/kolena) repository contains a runnable
-[example](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/search_embeddings) for embeddings extraction and
+[example](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/search_embeddings) for embeddings extraction and
 upload. This builds off the data uploaded in the
-[age_estimation](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/age_estimation) example workflow, and is best
+[age_estimation](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/age_estimation) example workflow, and is best
 run after this data has been uploaded to your Kolena environment.
 
 ## How to Set Up Natural Language Search

docs/reference/dataset/index.md

@@ -7,5 +7,5 @@ hide:
 # :kolena-dataset-20: `kolena.dataset`
 
 <div class="grid cards" markdown>
-- :kolena-developer-16: Examples: [`kolena/examples/dataset` ↗](https://github.com/kolenaIO/kolena/tree/trunk/examples)
+- :kolena-developer-16: Examples: [`kolena/examples/dataset` ↗](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples)
 </div>

docs/reference/pre-built/classification.md

@@ -29,15 +29,15 @@ This pre-built workflow is work in progress; however, you can refer to the workf
 and **multiclass** types from the examples below:
 
 <div class="grid cards" markdown>
-- [:kolena-classification-20: Example: Binary Classification](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/classification#binary-classification-on-dogs-vs-cats)
+- [:kolena-classification-20: Example: Binary Classification](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/classification#binary-classification-on-dogs-vs-cats)
 
     !["Dog" classification example from the Dogs vs. Cats dataset.](../../assets/images/classification-dog.jpg)
 
     ---
 
     Binary Classification of class "Dog" using the [Dogs vs. Cats](https://www.kaggle.com/c/dogs-vs-cats) dataset
 
-- [:kolena-classification-20: Example: Multiclass Classification](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/classification#multiclass-classification-on-cifar-10)
+- [:kolena-classification-20: Example: Multiclass Classification](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/classification#multiclass-classification-on-cifar-10)
 
     ![Example images from CIFAR-10 dataset.](../../assets/images/CIFAR-10.jpg)
 

docs/reference/pre-built/object-detection-2d.md

@@ -20,7 +20,7 @@ This pre-built workflow is prepared for a 2D Object Detection problem and here i
 on the COCO dataset.
 
 <div class="grid cards" markdown>
-- [:kolena-widget-20: Example: Object Detection (2D) ↗](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/object_detection_2d)
+- [:kolena-widget-20: Example: Object Detection (2D) ↗](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/object_detection_2d)
 
     ![Example 2D bounding boxes from the COCO dataset.](../../assets/images/COCO-transportation.jpeg)
 

docs/reference/workflow/index.md

@@ -15,7 +15,7 @@ hide:
 
 <div class="grid cards" markdown>
 - :kolena-layers-16: Developer Guide: [Building a Workflow ↗](../../workflow/building-a-workflow.md)
-- :kolena-developer-16: Examples: [`kolena/examples` ↗](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow)
+- :kolena-developer-16: Examples: [`kolena/examples` ↗](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow)
 </div>
 
 `kolena.workflow` contains the definitions to build a [workflow](../../workflow/core-concepts/workflow.md):

docs/workflow/core-concepts/workflow.md

@@ -19,9 +19,9 @@ can be tested can be modeled as a workflow in Kolena.
 Examples of workflows include:
 
 <div class="grid cards" markdown>
-- [:kolena-widget-20: Object Detection (2D)](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/object_detection_2d) using images
-- [:kolena-text-summarization-20: Text Summarization](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/text_summarization) using articles/documents
-- [:kolena-age-estimation-20: Age Estimation](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/age_estimation) (regression) using images
+- [:kolena-widget-20: Object Detection (2D)](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/object_detection_2d) using images
+- [:kolena-text-summarization-20: Text Summarization](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/text_summarization) using articles/documents
+- [:kolena-age-estimation-20: Age Estimation](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/age_estimation) (regression) using images
 - [:kolena-video-20: Video Retrieval](https://paperswithcode.com/task/video-retrieval) using text queries on a corpus of videos
 </div>
 

docs/workflow/quickstart.md

@@ -14,7 +14,7 @@ icon: kolena/flame-16
 Install Kolena to set up rigorous and repeatable model testing in minutes.
 
 In this quickstart guide, we'll use the
-[`object_detection_2d`](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/object_detection_2d) example integration to
+[`object_detection_2d`](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/object_detection_2d) example integration to
 demonstrate the how to curate test data and test models in Kolena.
 
 ## Install `kolena`
@@ -40,23 +40,23 @@ and run directly:
 
 <div class="grid cards" markdown>
 
-- [:kolena-fr-20: Example: Face Recognition 1:1 ↗](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/face_recognition_11)
+- [:kolena-fr-20: Example: Face Recognition 1:1 ↗](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/face_recognition_11)
 
     ![Example image from Face Recognition 1:1 Workflow.](../assets/images/fr11.jpg)
 
     ---
 
     End-to-end face recognition 1:1 using the [Labeled Faces in the Wild (LFW)](http://vis-www.cs.umass.edu/lfw/) dataset.
 
-- [:kolena-age-estimation-20: Example: Age Estimation ↗](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/age_estimation)
+- [:kolena-age-estimation-20: Example: Age Estimation ↗](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/age_estimation)
 
     ![Example images from the Labeled Faces in the Wild dataset.](../assets/images/LFW.jpg)
 
     ---
 
     Age Estimation using the [Labeled Faces in the Wild (LFW)](http://vis-www.cs.umass.edu/lfw/) dataset
 
-- [:kolena-keypoint-detection-20: Example: Keypoint Detection ↗](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/keypoint_detection)
+- [:kolena-keypoint-detection-20: Example: Keypoint Detection ↗](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/keypoint_detection)
 
     ![Example image and five-point facial keypoints array from the 300 Faces in the Wild dataset.](../assets/images/300-W.jpg)
 
@@ -65,7 +65,7 @@ and run directly:
     Facial Keypoint Detection using the [300 Faces in the Wild (300-W)](https://ibug.doc.ic.ac.uk/resources/300-W/)
     dataset
 
-- [:kolena-text-summarization-20: Example: Text Summarization ↗](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/text_summarization)
+- [:kolena-text-summarization-20: Example: Text Summarization ↗](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/text_summarization)
 
     ![Example articles from the CNN-DailyMail dataset.](../assets/images/CNN-DailyMail.jpg)
 
@@ -74,47 +74,47 @@ and run directly:
     Text Summarization using [OpenAI GPT-family models](https://platform.openai.com/docs/guides/gpt) and the
     [CNN-DailyMail](https://paperswithcode.com/dataset/cnn-daily-mail-1) dataset
 
-- [:kolena-widget-20: Example: Object Detection (2D) ↗](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/object_detection_2d)
+- [:kolena-widget-20: Example: Object Detection (2D) ↗](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/object_detection_2d)
 
     ![Example 2D bounding boxes from the COCO dataset.](../assets/images/COCO-transportation.jpeg)
 
     ---
 
     2D Object Detection using the [COCO](https://cocodataset.org/#overview) dataset
 
-- [:kolena-drive-time-20: Example: Object Detection (3D) ↗](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/object_detection_3d)
+- [:kolena-drive-time-20: Example: Object Detection (3D) ↗](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/object_detection_3d)
 
     ![Example pointcloud and 3D object bounding boxes from the KITTI dataset.](../assets/images/KITTI-pointcloud.png)
 
     ---
 
     3D Object Detection using the [KITTI](https://www.cvlibs.net/datasets/kitti/eval_object.php?obj_benchmark=3d) dataset
 
-- [:kolena-classification-20: Example: Binary Classification ↗](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/classification#binary-classification-on-dogs-vs-cats)
+- [:kolena-classification-20: Example: Binary Classification ↗](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/classification#binary-classification-on-dogs-vs-cats)
 
     !["Dog" classification example from the Dogs vs. Cats dataset.](../assets/images/classification-dog.jpg)
 
     ---
 
     Binary Classification of class "Dog" using the [Dogs vs. Cats](https://www.kaggle.com/c/dogs-vs-cats) dataset
 
-- [:kolena-classification-20: Example: Multiclass Classification ↗](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/classification#multiclass-classification-on-cifar-10)
+- [:kolena-classification-20: Example: Multiclass Classification ↗](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/classification#multiclass-classification-on-cifar-10)
 
     ![Example images from CIFAR-10 dataset.](../assets/images/CIFAR-10.jpg)
 
     ---
 
     Multiclass Classification using the [CIFAR-10](https://www.cs.toronto.edu/~kriz/cifar.html) dataset
 
-- [:kolena-comparison-20: Example: Semantic Textual Similarity ↗](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/semantic_textual_similarity)
+- [:kolena-comparison-20: Example: Semantic Textual Similarity ↗](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/semantic_textual_similarity)
 
     ![Example sentence pairs from STS benchmark dataset.](../assets/images/STS-benchmark.jpg)
 
     ---
 
     Semantic Textual Similarity using the [STS benchmark](http://ixa2.si.ehu.eus/stswiki/index.php/STSbenchmark) dataset
 
-- [:kolena-chat-20: Example: Question Answering ↗](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/question_answering)
+- [:kolena-chat-20: Example: Question Answering ↗](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/question_answering)
 
     ![Example questions from CoQA dataset.](../assets/images/CoQA.jpg)
 
@@ -123,7 +123,7 @@ and run directly:
     Question Answering using the
     [Conversational Question Answering (CoQA)](https://stanfordnlp.github.io/coqa/) dataset
 
-- [:kolena-polygon-20: Example: Semantic Segmentation ↗](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/semantic_segmentation)
+- [:kolena-polygon-20: Example: Semantic Segmentation ↗](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/semantic_segmentation)
 
     ![Example image from COCO-Stuff 10K dataset.](../assets/images/coco-stuff-10k.jpg)
 
@@ -132,7 +132,7 @@ and run directly:
     Semantic Segmentation on class `Person` using the
     [COCO-Stuff 10K](https://github.com/nightrome/cocostuff10k) dataset
 
-- [:kolena-audio-workflow-20: Example: Automatic Speech Recognition ↗](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/automatic_speech_recognition)
+- [:kolena-audio-workflow-20: Example: Automatic Speech Recognition ↗](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/automatic_speech_recognition)
 
     ![Example image from the automatic speech recognition workflow.](../assets/images/librispeech-workflow-example.png)
 
@@ -141,7 +141,7 @@ and run directly:
     Automatic speech recognition using the
     [LibriSpeech](https://www.openslr.org/12) dataset
 
-- [:kolena-diarization-workflow-20: Example: Speaker Diarization ↗](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/speaker_diarization)
+- [:kolena-diarization-workflow-20: Example: Speaker Diarization ↗](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/speaker_diarization)
 
     ![Example image from the speaker diarization workflow.](../assets/images/speaker-diarization-example.png)
 
@@ -159,7 +159,7 @@ git clone https://github.com/kolenaIO/kolena.git
 ```
 
 With the repository cloned, let's set up the
-[`object_detection_2d`](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/object_detection_2d) example:
+[`object_detection_2d`](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/object_detection_2d) example:
 
 ```shell
 cd kolena/examples/workflow/object_detection_2d

examples/workflow/README.md

@@ -14,9 +14,9 @@ arbitrary ML problem.
   [KITTI](https://www.cvlibs.net/datasets/kitti/eval_object.php?obj_benchmark=3d) dataset
 - [Text Summarization](./text_summarization): abstractive text summarization using the
   [CNN-DailyMail](https://paperswithcode.com/dataset/cnn-daily-mail-1) dataset
-- [Mutliclass Classification](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/classification#multiclass-classification-on-cifar-10): Multiclass Classification
+- [Mutliclass Classification](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/classification#multiclass-classification-on-cifar-10): Multiclass Classification
   on image data from [CIFAR-10](https://www.cs.toronto.edu/~kriz/cifar.html) dataset
-- [Binary Classification](https://github.com/kolenaIO/kolena/tree/trunk/examples/workflow/classification#binary-classification-on-dogs-vs-cats):
+- [Binary Classification](https://github.com/kolenaIO/kolena/tree/hotfix/0.100.x/examples/workflow/classification#binary-classification-on-dogs-vs-cats):
   Binary Classification on image data from [Dogs vs. Cats](https://www.kaggle.com/c/dogs-vs-cats) dataset
 - [Semantic Textual Similarity](./semantic_textual_similarity): semantic textual similarity using the
   [STS Benchmark](http://ixa2.si.ehu.eus/stswiki/index.php/STSbenchmark) dataset