Add title

app.ipynb

@@ -368,6 +368,17 @@
     "df.tail()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "title = \"\"\"<h1 align=\"center\">The Large Language Models Landscape</h1>\"\"\"\n",
+    "description = \"\"\"Large Language Models (LLMs) today come in a variety architectures and capabilities. This interactive landscape provides a visual overview of the most important LLMs, including their training data, size, release date, and whether they are openly accessible or not. It also includes notes on each model to provide additional context. This landscape is derived from data compiled by Dr. Alan D. Thompson at [lifeaarchitext.ai](https://lifearchitect.ai).\n",
+    "\"\"\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 26,
@@ -409,6 +420,8 @@
     "    return df\n",
     "\n",
     "with gr.Blocks() as demo:\n",
+    "    gr.Markdown(title)\n",
+    "    gr.Markdown(description)\n",
     "    gr.DataFrame(value=value_func)\n",
     "\n",
     "demo.launch()"
@@ -433,7 +446,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [],
    "source": [

app.py

@@ -18,11 +18,13 @@ df = df.copy()[~df["Model"].isna()]
 # Drop TBA models
 df = df.copy()[df["Parameters \n(B)"] != "TBA"]
 
-# %% app.ipynb 6
+# %% app.ipynb 7
 def value_func():
     return df
 
 with gr.Blocks() as demo:
+    gr.Markdown(title)
+    gr.Markdown(description)
     gr.DataFrame(value=value_func)
 
 demo.launch()