update

app.py

@@ -45,7 +45,7 @@ st.markdown(
 )
 df = pd.read_csv("utils/data_preview.csv")
 st.dataframe(df)
-st.header("Model")
+st.subheader("Model")
 col1, col2= st.columns([1,2])
 with col1:
     selected_model = st.selectbox(
@@ -58,7 +58,7 @@ st.markdown(text)
 # Model architecture
 st.title("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.header("Model")
+st.subheader("Model")
 col1, col2= st.columns([1,2])
 with col1:
     selected_model = st.selectbox(
@@ -78,13 +78,13 @@ st.markdown(intro)
 
 # Code generation
 st.title("4 - Code generation 💻")
-col1, col2 = st.columns(2)
+col1, col2, col3 = st.columns([5,1,5])
 with col1:
-    st.subheader("Models")
+    st.markdown("**Models**")
     selected_models = st.multiselect(
     "Select code generation models to compare", MODELS, default=["CodeParrot"], key=3
 )
-    st.subheader("Examples")
+    st.markdown("**Examples**")
     examples = load_examples()
     example_names = [example["name"] for example in examples]
     name2id = dict([(name, i) for i, name in enumerate(example_names)])
@@ -93,8 +93,8 @@ with col1:
     )
     example_text = examples[name2id[selected_example]]["value"]
     default_length = examples[name2id[selected_example]]["length"]
-with col2:
-    st.subheader("Generation settings")
+with col3:
+    st.markdown("**Generation settings**")
     temperature = st.slider(
         "Temperature:", value=0.2, min_value=0.0, step=0.1, max_value=2.0
     )
@@ -111,7 +111,7 @@ with col2:
 gen_prompt = st.text_area(
     "Generate code with prompt:",
     value=example_text,
-    height=220,
+    height=150,
 ).strip()
 if st.button("Generate code!"):
     with st.spinner("Generating code..."):