update

app.py

@@ -59,6 +59,7 @@ st.markdown(text)
 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")
+col1, col2= st.columns([1,2])
 with col1:
     selected_model = st.selectbox(
     "Select a code generation model", MODELS, key=2
@@ -77,51 +78,53 @@ st.markdown(intro)
 
 # Code generation
 st.title("4 - Code generation 💻")
-st.header("Models")
+col1, col2 = st.columns(2)
 with col1:
+    st.subheader("Models")
     selected_models = st.multiselect(
     "Select code generation models to compare", MODELS, default=["CodeParrot"], key=3
 )
-st.header("Examples")
-examples = load_examples()
-example_names = [example["name"] for example in examples]
-name2id = dict([(name, i) for i, name in enumerate(example_names)])
-selected_example = st.selectbox(
-    "Select one of the following examples or implement yours", example_names
-)
-example_text = examples[name2id[selected_example]]["value"]
-default_length = examples[name2id[selected_example]]["length"]
-st.header("Generation settings")
-temperature = st.slider(
-    "Temperature:", value=0.2, min_value=0.0, step=0.1, max_value=2.0
-)
-max_new_tokens = st.slider(
-    "Number of tokens to generate:",
-    value=default_length,
-    min_value=8,
-    step=8,
-    max_value=256,
-)
-seed = st.slider(
-    "Random seed:", value=42, min_value=0, step=1, max_value=1000
-)
-gen_prompt = st.text_area(
-    "Generate code with prompt:",
-    value=example_text,
-    height=220,
-).strip()
-if st.button("Generate code!"):
-    with st.spinner("Generating code..."):
-        # Create a multiprocessing Pool
-        pool = Pool()
-        generate_parallel = partial(
-            generate_code,
-            gen_prompt=gen_prompt,
-            max_new_tokens=max_new_tokens,
-            temperature=temperature,
-            seed=seed,
-        )
-        output = pool.map(generate_parallel, selected_models)
-        for i in range(len(output)):
-            st.markdown(f"**{selected_models[i]}**")
-            st.code(output[i])
+    st.subheader("Examples")
+    examples = load_examples()
+    example_names = [example["name"] for example in examples]
+    name2id = dict([(name, i) for i, name in enumerate(example_names)])
+    selected_example = st.selectbox(
+        "Select one of the following examples or implement yours", example_names
+    )
+    example_text = examples[name2id[selected_example]]["value"]
+    default_length = examples[name2id[selected_example]]["length"]
+    st.subheader("Generation settings")
+    temperature = st.slider(
+        "Temperature:", value=0.2, min_value=0.0, step=0.1, max_value=2.0
+    )
+    max_new_tokens = st.slider(
+        "Number of tokens to generate:",
+        value=default_length,
+        min_value=8,
+        step=8,
+        max_value=256,
+    )
+    seed = st.slider(
+        "Random seed:", value=42, min_value=0, step=1, max_value=1000
+    )
+with col2:
+    gen_prompt = st.text_area(
+        "Generate code with prompt:",
+        value=example_text,
+        height=220,
+    ).strip()
+    if st.button("Generate code!"):
+        with st.spinner("Generating code..."):
+            # Create a multiprocessing Pool
+            pool = Pool()
+            generate_parallel = partial(
+                generate_code,
+                gen_prompt=gen_prompt,
+                max_new_tokens=max_new_tokens,
+                temperature=temperature,
+                seed=seed,
+            )
+            output = pool.map(generate_parallel, selected_models)
+            for i in range(len(output)):
+                st.markdown(f"**{selected_models[i]}**")
+                st.code(output[i])