update

app.py

@@ -39,13 +39,12 @@ with open("utils/intro.txt", "r") as f:
 st.markdown(intro)
 
 # Pretraining datasets
-st.title("1 - Pretraining datasets 📚")
+st.subheader("1 - Pretraining datasets 📚")
 st.markdown(
     f"Preview of some code files from Github repositories in [Github-code dataset]({GITHUB_CODE}):"
 )
 df = pd.read_csv("utils/data_preview.csv")
 st.dataframe(df)
-st.subheader("Model")
 col1, col2= st.columns([1,2])
 with col1:
     selected_model = st.selectbox(
@@ -56,9 +55,8 @@ with open(f"datasets/{selected_model.lower()}.txt", "r") as f:
 st.markdown(text)
 
 # Model architecture
-st.title("2 - Model architecture")
+st.subheader("2 - Model architecture")
 st.markdown("Most code generation models use GPT style architectures trained on code. Some use encoder-decoder architectures such as AlphaCode.")
-st.subheader("Model")
 col1, col2= st.columns([1,2])
 with col1:
     selected_model = st.selectbox(
@@ -71,13 +69,13 @@ if selected_model == "InCoder":
     st.image(INCODER_IMG, caption="Figure 1: InCoder training", width=700)
 
 # Model evaluation
-st.title("3 - Code models evaluation 📊")
+st.subheader("3 - Code models evaluation 📊")
 with open("evaluation/intro.txt", "r") as f:
     intro = f.read()
 st.markdown(intro)
 
 # Code generation
-st.title("4 - Code generation 💻")
+st.subheader("4 - Code generation ✨")
 col1, col2, col3 = st.columns([5,1,5])
 with col1:
     st.markdown("**Models**")