Update app.py

app.py

@@ -45,6 +45,53 @@ def refresh_leaderboard():
     else:
         return process_df(leaderboard_df)
 
+# Usage markdown
+usage = """
+
+## Using the web interface
+
+Run your model on the evaluation datasets and create a json file in this format:
+```
+[
+    {
+        "Model": "whisperbase",
+        "date": "",
+        "ucfd_eng": 102.27,
+        "ucfd_lug": "nan",
+        "sema_eng" : 42.86,
+        "sema_lug": "nan",
+        "trac_fm_lug": "nan",
+        "Link": "https://colab.research.google.com/drive/1MGGOotrjSXWkR3ljNEVvfEUResEx6OLV#scrollTo=Elwx1K3fEDjf"
+    },
+    {
+        "Model": "facebookmms",
+        "date": "2024-06-26",
+        "ucfd_eng": 92.91,
+        "ucfd_lug": "nan",
+        "sema_eng" : 63.39,
+        "sema_lug": "nan",
+        "trac_fm_lug": 69.29,
+        "Link": "https://colab.research.google.com/drive/1MGGOotrjSXWkR3ljNEVvfEUResEx6OLV#scrollTo=Elwx1K3fEDjf"
+    }
+]
+```
+>Upload this to the leaderboard and it should be updated with your results.
+
+## Using the API
+
+You can use the following code to programmatically upload your results from a colab or python script.
+```
+from gradio_client import Client, handle_file
+
+client = Client("sunbird/SB_ASR_Leaderboard")
+result = client.predict(
+		jsonfile=handle_file([/path/to/eval_results.json]),
+		api_name="/get_eval"
+)
+```
+>Refresh the leaderboard and your results should be visible.
+"""
+
 # Initialize an empty dataframe for the leaderboard
 columns = ['Model', 'date', 'ucfd_eng', 'ucfd_lug',
            'sema_eng', 'sema_lug', 'trac_fm_lug']
@@ -63,6 +110,9 @@ with block:
         with gr.TabItem("ASR Leaderboard"):
             with gr.Row():
                 data = gr.DataFrame(datatype="markdown")
+        with gr.TabItem("Usage"):
+            with gr.Row():
+                gr.Markdown(usage)
                 
     input_json.upload(get_eval, inputs=input_json, outputs=data)