docs: ReadMe updates for tutorials (#612)

Co-authored-by: caitlinwheeless <[email protected]>

label_studio_ml/examples/segment_anything_2_image/README.md

@@ -72,7 +72,7 @@ $ curl http://localhost:9090/
 3. Connect to the backend from Label Studio running on the same host: go to your project `Settings -> Machine Learning -> Add Model` and specify `http://localhost:9090` as a URL.
 
 
-# Configuration
+## Configuration
 Parameters can be set in `docker-compose.yml` before running the container.
 
 
@@ -86,6 +86,6 @@ The following common parameters are available:
 - `WORKERS` - specify the number of workers for the model server
 - `THREADS` - specify the number of threads for the model server
 
-# Customization
+## Customization
 
 The ML backend can be customized by adding your own models and logic inside the `./segment_anything_2` directory. 

label_studio_ml/examples/segment_anything_2_video/README.md

@@ -55,7 +55,8 @@ Note that if you're running in a cloud server, you'll need to run on an exposed
 
 # Labeling Config
 For your project, you can use any labeling config with video properties. Here's a basic one to get you started!
-
+
+```xml     
     <View>
          <Labels name="videoLabels" toName="video" allowEmpty="true">
 
@@ -69,15 +70,16 @@ For your project, you can use any labeling config with video properties. Here's
       </View><!--{
        "video": "/static/samples/opossum_snow.mp4"
       }-->
+```
 
-
-# Known limitations
+## Known limitations
 - As of 8/11/2024, SAM2 only runs on GPU servers. 
 - Currently, we only support the tracking of one object in video, although SAM2 can support multiple. 
 - Currently, we do not support video segmentation. 
 - No Docker support
 
 If you want to contribute to this repository to help with some of these limitations, you can submit a PR. 
-# Customization
+
+## Customization
 
 The ML backend can be customized by adding your own models and logic inside the `./segment_anything_2_video` directory. 

label_studio_ml/examples/watsonx_llm/README.md

@@ -6,12 +6,11 @@ tier: all
 order: 15
 hide_menu: true
 hide_frontmatter_title: true
-meta_title: Using WatsonX with Label Studio
+meta_title: Integrate WatsonX with Label Studio
 categories:
     - Computer Vision
-    - Video Annotation
-    - Object Detection
-    - Segment Anything Model
+    - Large Language Model
+    - WatsonX
 image: "/tutorials/watsonx.png"
 ---
 -->
@@ -32,12 +31,11 @@ See the configuration notes at the bottom for details on how to set up your envi
 
 For a video demonstration, see [Integrating Label Studio with IBM WatsonX](https://www.youtube.com/watch?v=9iP2yO4Geqc).
 
-<video src="https://www.youtube.com/watch?v=9iP2yO4Geqc" controls="controls" style="max-width: 800px;" class="gif-border" />
-
 ## Setting up your label_config
 For this project, we recommend you start with the labeling config as defined below, but you can always edit it or expand it to
 meet your needs! Crucially, there must be a `<TextArea>` tag for the model to insert its response into. 
 
+```xml
     <View>
         <Style>
             .lsf-main-content.lsf-requesting .prompt::before { content: ' loading...'; color: #808080; }
@@ -81,7 +79,7 @@ meet your needs! Crucially, there must be a `<TextArea>` tag for the model to in
         <Header value="Overall response quality:"/>
         <Rating name="rating" toName="context"/>
     </View>
-
+```
 
 ## Setting up WatsonX.Data
 To use your WatsonX.data integration, follow the steps below. 
@@ -159,7 +157,7 @@ The following parameters allow you to link the WatsonX models to Label Studio:
 
 The following parameters allow you to use the webhook connection to transfer data from Label Studio to WatsonX.data:
 
--`WATSONX_ENG_USERNAME`- MUST be `ibmlhapikey` for the integration to work.
+- `WATSONX_ENG_USERNAME`- MUST be `ibmlhapikey` for the integration to work.
 
 To get the host and port information below, you can follow the steps under [Pre-requisites](https://cloud.ibm.com/docs/watsonxdata?topic=watsonxdata-con-presto-serv#conn-to-prestjava).