input gif

app.py

@@ -28,19 +28,27 @@ st.markdown("**Why does this matter?** Through echo chambers, polarization, and
 st.markdown("How is climate change misinformation combatted now? Below are a few of the ways according to the Brookings Institute:")
 st.markdown("1. Asking news sources to call out misinformation")
 st.markdown("2. Teaching and encouraging media literacy among the public (how to detect fake news, critical evaluation of information provided, etc.")
-st.markdown("2. Government ")
-st.markdown("3. Fact-checking")
+st.markdown("3. Governments should encourage independent journalism but avoid censoring news")
 st.markdown("4. Social media platform investment in algorithmic detection of fake news")
 
 st.markdown("However, many of the proposed solutions above require adoption of behaviors. This is difficult to acheive, particularly among news organizations and social media platforms which receive monetary benefits from misinformation in the form of ad revenue from cite usage and viewership.")
 
 # section 3: how can transformers help?
+st.markdown("### How can Transformers Help?")
+
 # fever dataset
 # entailment/contradiction/neutral adoption to support/refute/n.e.i.
 # extention to climate
 
 # section 4: The process
 # this is the pipeline in my notes (u are here highlight)
+st.markdown("### The Process")
+
+st.markdown("Imagine: A person is curious about whether a claim they heard about climate change is true. How can transformers help validate or refute the claim?")
+
+st.markdown("1. User inputs a climate claim")
+input_gif = Image.open('images/input_box.gif')
+st.image(input_gif)
 
 # section 5: my work