slight refactor in markdown

app.py

@@ -7,13 +7,7 @@ suite = evaluate.EvaluationSuite.load("Vipitis/ShaderEval") #downloads it
 # from ShaderEval import Suite
 # suite = Suite("Vipitis/ShaderEval")
 
-def run_suite(model_cp, snippet):
-    # print(model_cp, snippet)
-    results = suite.run(model_cp, snippet)
-    return results[0]
-
-with gr.Blocks() as site:
-    text = gr.Markdown("""# Welcome to the ShaderEval Suite.
+text = """# Welcome to the ShaderEval Suite.
             
             This space hosts the ShaderEval Suite. more to follow soon.
             
@@ -38,7 +32,7 @@ with gr.Blocks() as site:
             
             ### try the demo below
             - Select a **model checkpoint** from the "dropdown"
-            - Select how many **samples** to run (there us up to 100 from the test set)
+            - Select how many **samples** to run (there us up to 200 from the test set)
             - Click **Run** to run the suite
             - The results will be displayed in the **Output** box
             
@@ -47,10 +41,19 @@ with gr.Blocks() as site:
             - supporting batches to speed up inference
             - CER metric 
             - removing the pad_token warning
+            - adding OpenVINO pipelines for inference, pending on OpenVINO release
             """
-            )
+
+
+def run_suite(model_cp, snippet):
+    # print(model_cp, snippet)
+    results = suite.run(model_cp, snippet)
+    return results[0]
+
+with gr.Blocks() as site:
+    text_md = gr.Markdown(text)
     model_cp = gr.Textbox(value="gpt2", label="Model Checkpoint", interactive=True)
-    first_n = gr.Slider(minimum=1, maximum=100, default=15, label="num_samples", step=1.0)
+    first_n = gr.Slider(minimum=1, maximum=200, default=15, label="num_samples", step=1.0)
     output = gr.Textbox(label="Output")
     run_button = gr.Button(label="Run")
     run_button.click(fn=run_suite, inputs=[model_cp, first_n], outputs=output)