fixing a bug in the partials template

Author: RyanMullins

docs/demos/index.html

@@ -119,15 +119,15 @@
   <div class="demo-card-cta-button"><a href="/lit/demos/glue.html"></a></div>
 </div>
 <div class="demo-card mdl-cell mdl-cell--6-col mdl-cell--4-col-tablet mdl-cell--4-col-phone">
-  <div class="demo-card-title"><a href="/lithttps://colab.research.google.com/github/PAIR-code/lit/blob/main/lit_nlp/examples/notebooks/LIT_sentiment_classifier.ipynb" target="_blank">Notebook usage</a></div>
+  <div class="demo-card-title"><a href="https://colab.research.google.com/github/PAIR-code/lit/blob/main/lit_nlp/examples/notebooks/LIT_sentiment_classifier.ipynb" target="_blank">Notebook usage</a></div>
   <div class="demo-card-tags"> <span class="demo-tag"> BERT </span>  <span class="demo-tag"> binary classification </span>  <span class="demo-tag"> notebooks </span> 
   </div>
-  <div class="demo-card-data-source-title">DATA SOURCES</div>
+  <div class="demo-card-data-source-title">DATA SOURCE</div>
   <div class="demo-card-data-source">
-    Stanford Sentiment Treebank
+    <a href="" target="_blank">Stanford Sentiment Treebank</a>
   </div>
   <div class="demo-card-copy">Use LIT directly inside a Colab notebook. Explore binary classification for sentiment analysis using SST2 from the General Language Understanding Evaluation (GLUE) benchmark suite.</div>
-  <div class="demo-card-cta-button"><a href="/lithttps://colab.research.google.com/github/PAIR-code/lit/blob/main/lit_nlp/examples/notebooks/LIT_sentiment_classifier.ipynb"></a></div>
+  <div class="demo-card-cta-button"><a href="https://colab.research.google.com/github/PAIR-code/lit/blob/main/lit_nlp/examples/notebooks/LIT_sentiment_classifier.ipynb"></a></div>
 </div>
 <div class="demo-card mdl-cell mdl-cell--6-col mdl-cell--4-col-tablet mdl-cell--4-col-phone">
   <div class="demo-card-title"><a href="/lit/demos/coref.html" target="_blank">Gender bias in coreference systems</a></div>

website/src/demos.md

@@ -18,12 +18,12 @@ color: "#49596c"
 
   {% include partials/demo-card c-title: "Image classification", link: "/demos/images.html",
   c-data-source: "Imagenette", c-copy: "Analyze an image classification model with LIT, including muliple image salience techniques.", tags: "images, mutli-class classification", external:"true" %}
-  
-  {% include partials/demo-card c-title: "Classification and regression models", link: "/demos/glue.html", 
+
+  {% include partials/demo-card c-title: "Classification and regression models", link: "/demos/glue.html",
   c-data-source: "Stanford Sentiment Treebank,  Multi-Genre NLI Corpus, Semantic Textual Similarity Benchmark"
   c-copy: "Use LIT with any of three tasks from the General Language Understanding Evaluation (GLUE) benchmark suite. This demo contains binary classification (for sentiment analysis, using SST2), multi-class classification (for textual entailment, using MultiNLI), and regression (for measuringtext similarity, using STS-B).", tags: "BERT, binary classification, multi-class classification, regression", external:"true" %}
 
-  {% include partials/demo-card c-title: "Notebook usage", link: "https://colab.research.google.com/github/PAIR-code/lit/blob/main/lit_nlp/examples/notebooks/LIT_sentiment_classifier.ipynb",
+  {% include partials/external-demo-card c-title: "Notebook usage", link: "https://colab.research.google.com/github/PAIR-code/lit/blob/main/lit_nlp/examples/notebooks/LIT_sentiment_classifier.ipynb",
   c-data-source: "Stanford Sentiment Treebank"
   c-copy: "Use LIT directly inside a Colab notebook. Explore binary classification for sentiment analysis using SST2 from the General Language Understanding Evaluation (GLUE) benchmark suite.", tags: "BERT, binary classification, notebooks", external:"true" %}