diff --git "a/app.ipynb" "b/app.ipynb"
--- "a/app.ipynb"
+++ "b/app.ipynb"
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "6003f943-4355-446f-a48a-2ceb3b194f35",
    "metadata": {},
    "outputs": [],
@@ -20,29 +20,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "id": "eda4b34e-199c-4358-baf8-235bc0b995c7",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'2.7.11'"
+       "('2.7.12', '0.8.6dev0', '0.10.2', '1.5.2')"
       ]
      },
-     "execution_count": null,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
+    "import toml\n",
     "import fastai\n",
-    "fastai.__version__"
+    "import timm\n",
+    "import pandas\n",
+    "fastai.__version__, timm.__version__ , toml.__version__, pandas.__version__"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "id": "dc77cb01-22f1-4d1c-bdd2-ab1caff5123a",
    "metadata": {},
    "outputs": [],
@@ -50,19 +53,21 @@
     "#| export\n",
     "from fastai.vision.all import *\n",
     "from huggingface_hub import from_pretrained_fastai\n",
-    "import gradio as gr"
+    "import gradio as gr\n",
+    "import wikipedia\n",
+    "import pandas as pd"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "f8bdf35f-049b-4554-b32c-b07f0095336c",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "dc081e18e6b545c985d52e0d13010ece",
+       "model_id": "f9c510daca78426eb98bc06971fd267f",
        "version_major": 2,
        "version_minor": 0
       },
@@ -76,7 +81,7 @@
    ],
    "source": [
     "#| export\n",
-    "repo_id = \"Jimmie/snake-image-classification\"\n",
+    "repo_id = \"Jimmie/snake-species-identification\"\n",
     "\n",
     "# loading the model from huggingface_hub\n",
     "learner = from_pretrained_fastai(repo_id)"
@@ -84,18 +89,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "id": "f2ee25de-552b-4f04-8a3c-ca009d67f55e",
    "metadata": {},
    "outputs": [],
    "source": [
     "#| export\n",
-    "path = Path('demo-images/')"
+    "path = Path('demo-images/')\n",
+    "countries = pd.read_csv('species_to_country_mapping.csv', index_col=0)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "id": "bd470688-5ed8-4620-9a9e-735ae0b8b79e",
    "metadata": {},
    "outputs": [
@@ -114,7 +120,7 @@
        " Path('demo-images/crotalus.jpg')]"
       ]
      },
-     "execution_count": null,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -125,120 +131,393 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "60ef514f-54f6-4363-911f-6797b99dbbd2",
+   "execution_count": 7,
+   "id": "aee8d52d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>afghanistan</th>\n",
+       "      <th>albania</th>\n",
+       "      <th>algeria</th>\n",
+       "      <th>angola</th>\n",
+       "      <th>anguilla</th>\n",
+       "      <th>antigua and barbuda</th>\n",
+       "      <th>argentina</th>\n",
+       "      <th>armenia</th>\n",
+       "      <th>aruba</th>\n",
+       "      <th>australia</th>\n",
+       "      <th>...</th>\n",
+       "      <th>uruguay</th>\n",
+       "      <th>usa</th>\n",
+       "      <th>uzbekistan</th>\n",
+       "      <th>vanuatu</th>\n",
+       "      <th>venezuela</th>\n",
+       "      <th>vietnam</th>\n",
+       "      <th>western sahara</th>\n",
+       "      <th>yemen</th>\n",
+       "      <th>zambia</th>\n",
+       "      <th>zimbabwe</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Acanthophis antarcticus</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Acanthophis cryptamydros</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Acanthophis hawkei</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Acanthophis laevis</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Acanthophis praelongus</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 195 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                          afghanistan  albania  algeria  angola  anguilla  \\\n",
+       "Acanthophis antarcticus             0        0        0       0         0   \n",
+       "Acanthophis cryptamydros            0        0        0       0         0   \n",
+       "Acanthophis hawkei                  0        0        0       0         0   \n",
+       "Acanthophis laevis                  0        0        0       0         0   \n",
+       "Acanthophis praelongus              0        0        0       0         0   \n",
+       "\n",
+       "                          antigua and barbuda  argentina  armenia  aruba  \\\n",
+       "Acanthophis antarcticus                     0          0        0      0   \n",
+       "Acanthophis cryptamydros                    0          0        0      0   \n",
+       "Acanthophis hawkei                          0          0        0      0   \n",
+       "Acanthophis laevis                          0          0        0      0   \n",
+       "Acanthophis praelongus                      0          0        0      0   \n",
+       "\n",
+       "                          australia  ...  uruguay  usa  uzbekistan  vanuatu  \\\n",
+       "Acanthophis antarcticus           1  ...        0    0           0        0   \n",
+       "Acanthophis cryptamydros          1  ...        0    0           0        0   \n",
+       "Acanthophis hawkei                1  ...        0    0           0        0   \n",
+       "Acanthophis laevis                0  ...        0    0           0        0   \n",
+       "Acanthophis praelongus            1  ...        0    0           0        0   \n",
+       "\n",
+       "                          venezuela  vietnam  western sahara  yemen  zambia  \\\n",
+       "Acanthophis antarcticus           0        0               0      0       0   \n",
+       "Acanthophis cryptamydros          0        0               0      0       0   \n",
+       "Acanthophis hawkei                0        0               0      0       0   \n",
+       "Acanthophis laevis                0        0               0      0       0   \n",
+       "Acanthophis praelongus            0        0               0      0       0   \n",
+       "\n",
+       "                          zimbabwe  \n",
+       "Acanthophis antarcticus          0  \n",
+       "Acanthophis cryptamydros         0  \n",
+       "Acanthophis hawkei               0  \n",
+       "Acanthophis laevis               0  \n",
+       "Acanthophis praelongus           0  \n",
+       "\n",
+       "[5 rows x 195 columns]"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "countries.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "f9197faa",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['australia', 'papua new guinea']"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sample_row = countries.loc[\"Acanthophis antarcticus\"]\n",
+    "# for sample_row, get all columns with a value of 1 and return them in a list\n",
+    "countries.loc[\"Acanthophis antarcticus\"][countries.loc[\"Acanthophis antarcticus\"] == 1].index.tolist()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "990423e0",
    "metadata": {},
    "outputs": [],
    "source": [
-    "snakes = get_image_files(path)"
+    "#| export\n",
+    "def get_countries(binomial):\n",
+    "    sample_row = countries.loc[binomial]\n",
+    "    country_list = sample_row[sample_row == 1].index.tolist()\n",
+    "    # title case all items in country_list\n",
+    "    country_list = [country.title() for country in country_list]\n",
+    "    # return all items in country_list as a string\n",
+    "    return \", \".join(country_list)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "fd671a4c-3f16-42d0-9df7-3302ab0da0eb",
+   "execution_count": 10,
+   "id": "71ac4e3d",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "PILImage mode=RGB size=192x146"
+       "'Australia, Papua New Guinea'"
       ]
      },
-     "execution_count": null,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "im = PILImage.create(snakes[0])\n",
-    "im.thumbnail((192,192))\n",
-    "im"
+    "get_countries(\"Acanthophis antarcticus\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "64f84ded-9fa6-4ad2-a998-5d81274cb253",
+   "execution_count": 11,
+   "id": "e19fab29",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Path('demo-images/masticophis.jpg')"
+       "'Australia'"
       ]
      },
-     "execution_count": null,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "snakes[0]"
+    "get_countries('Acanthophis hawkei')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "364db435-5d30-43af-8814-e953600535b6",
+   "execution_count": 12,
+   "id": "60ef514f-54f6-4363-911f-6797b99dbbd2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "snakes = get_image_files(path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "fd671a4c-3f16-42d0-9df7-3302ab0da0eb",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "text/html": [
-       "\n",
-       "<style>\n",
-       "    /* Turns off some styling */\n",
-       "    progress {\n",
-       "        /* gets rid of default border in Firefox and Opera. */\n",
-       "        border: none;\n",
-       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
-       "        background-size: auto;\n",
-       "    }\n",
-       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
-       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
-       "    }\n",
-       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
-       "        background: #F44336;\n",
-       "    }\n",
-       "</style>\n"
-      ],
+      "image/png": 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",
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "PILImage mode=RGB size=192x146"
       ]
      },
+     "execution_count": 13,
      "metadata": {},
-     "output_type": "display_data"
-    },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "im = PILImage.create(snakes[0])\n",
+    "im.thumbnail((192,192))\n",
+    "im"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "64f84ded-9fa6-4ad2-a998-5d81274cb253",
+   "metadata": {},
+   "outputs": [
     {
      "data": {
-      "text/html": [],
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "Path('demo-images/masticophis.jpg')"
       ]
      },
+     "execution_count": 14,
      "metadata": {},
-     "output_type": "display_data"
-    },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "snakes[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "364db435-5d30-43af-8814-e953600535b6",
+   "metadata": {},
+   "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Prediction of the genus: Masticophis\n",
-      "Probability: 88.28%\n"
+      "Prediction of the genus: Masticophis flagellum\n",
+      "Probability: 97.19%\n",
+      "Countries: Mexico, Turkey, Usa\n",
+      "Masticophis flagellum is a species of nonvenomous colubrid snake, commonly referred to as the coachwhip or the whip snake, which is endemic to the United States and Mexico. Six subspecies are recognized, including the nominotypical subspecies.\n"
      ]
     }
    ],
    "source": [
     "pred,idx,probs = learner.predict(im)\n",
     "print(f\"Prediction of the genus: {pred}\")\n",
-    "print(f\"Probability: {100*probs[idx].item():.2f}%\")"
+    "print(f\"Probability: {100*probs[idx].item():.2f}%\")\n",
+    "print(f\"Countries: {get_countries(pred)}\")\n",
+    "print(wikipedia.summary(pred))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "id": "1ed7a818-dc3c-4d67-937d-d142caf674f1",
    "metadata": {},
    "outputs": [
@@ -248,7 +527,7 @@
        "Path('demo-images/agkistrodon.png')"
       ]
      },
-     "execution_count": null,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -259,65 +538,35 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "id": "bd71a128-18f4-4bee-a0c1-86e719d941cc",
    "metadata": {},
    "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<style>\n",
-       "    /* Turns off some styling */\n",
-       "    progress {\n",
-       "        /* gets rid of default border in Firefox and Opera. */\n",
-       "        border: none;\n",
-       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
-       "        background-size: auto;\n",
-       "    }\n",
-       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
-       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
-       "    }\n",
-       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
-       "        background: #F44336;\n",
-       "    }\n",
-       "</style>\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Prediction of the genus: Agkistrodon\n",
-      "Probability: 91.21%\n"
+      "Prediction of the genus: Agkistrodon contortrix\n",
+      "Probability: 100.00%\n",
+      "Countries: Mexico, Usa\n",
+      "The eastern copperhead (Agkistrodon contortrix), also known as the copperhead, is a species of venomous snake, a pit viper, endemic to eastern North America; it is a member of the subfamily Crotalinae in the family Viperidae.\n",
+      "The eastern copperhead has distinctive, dark brown, hourglass-shaped markings, overlaid on a light reddish brown or brown/gray background. The body type is heavy, rather than slender. Neonates are born with green or yellow tail tips, which progress to a darker brown or black within one year. Adults grow to a typical length (including tail) of 50–95 cm (20–37 in).\n",
+      "In most of North America, it favors deciduous forest and mixed woodlands. It may occupy rock outcroppings and ledges, but is also found in low-lying, swampy regions. During the winter, it hibernates in dens or limestone crevices, often together with timber rattlesnakes and black rat snakes. The eastern copperhead is known to feed on a wide variety of prey, including invertebrates (primarily arthropods) and vertebrates. Like most pit vipers, the eastern copperhead is generally an ambush predator; it takes up a promising position and waits for suitable prey to arrive.\n",
+      "As a common species within its range, it may be encountered by humans. Unlike other viperids, they often \"freeze\" instead of slithering away, due to its habit of relying on excellent camouflage, rather than fleeing. Bites occur due to people unknowingly stepping on or near them.Five subspecies have been recognized in the past, but recent genetic analysis had yielded new species information.\n"
      ]
     }
    ],
    "source": [
     "pred,idx,probs = learner.predict(snakes[2])\n",
     "print(f\"Prediction of the genus: {pred}\")\n",
-    "print(f\"Probability: {100*probs[idx].item():.2f}%\")"
+    "print(f\"Probability: {100*probs[idx].item():.2f}%\")\n",
+    "print(f\"Countries: {get_countries(pred)}\")\n",
+    "print(wikipedia.summary(pred))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "id": "9fb6688e-ebc8-4718-8793-5f073c46bd89",
    "metadata": {},
    "outputs": [
@@ -327,7 +576,7 @@
        "Path('demo-images/nerodia.jpg')"
       ]
      },
-     "execution_count": null,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -338,65 +587,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "id": "bae66287-589f-476d-925c-02ce34aeb70b",
    "metadata": {},
    "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<style>\n",
-       "    /* Turns off some styling */\n",
-       "    progress {\n",
-       "        /* gets rid of default border in Firefox and Opera. */\n",
-       "        border: none;\n",
-       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
-       "        background-size: auto;\n",
-       "    }\n",
-       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
-       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
-       "    }\n",
-       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
-       "        background: #F44336;\n",
-       "    }\n",
-       "</style>\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Prediction of the genus: Nerodia\n",
-      "Probability: 64.35%\n"
+      "Prediction of the genus: Nerodia rhombifer\n",
+      "Probability: 99.91%\n",
+      "Countries: Belize, Guatemala, Mexico, Usa\n",
+      "Nerodia rhombifer, commonly known as the diamondback water snake, is a species of nonvenomous natricine colubrid endemic to the central United States and northern Mexico. There are three recognized subspecies of N. rhombifer, including the nominotypical subspecies.\n"
      ]
     }
    ],
    "source": [
     "pred,idx,probs = learner.predict(snakes[7])\n",
     "print(f\"Prediction of the genus: {pred}\")\n",
-    "print(f\"Probability: {100*probs[idx].item():.2f}%\")"
+    "print(f\"Probability: {100*probs[idx].item():.2f}%\")\n",
+    "print(f\"Countries: {get_countries(pred)}\")\n",
+    "print(wikipedia.summary(pred))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "id": "797ec0c4-db66-4312-9d67-d4e008fbca0c",
    "metadata": {},
    "outputs": [],
@@ -406,68 +622,77 @@
     "\n",
     "def classify_image(img):\n",
     "    pred,idx,probs = learner.predict(img)\n",
-    "    return dict(zip(categories, map(float, probs)))"
+    "    countries = get_countries(pred)\n",
+    "    summary = wikipedia.summary(pred)\n",
+    "    wiki_link = f\"Learn more: <a href={wikipedia.page(pred).url}> {pred}</a>\"\n",
+    "    return dict(zip(categories, map(float, probs))), countries, summary, wiki_link"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "id": "0a9cf1d8-b2ac-44a1-88f3-778814fe69c5",
    "metadata": {},
    "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<style>\n",
-       "    /* Turns off some styling */\n",
-       "    progress {\n",
-       "        /* gets rid of default border in Firefox and Opera. */\n",
-       "        border: none;\n",
-       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
-       "        background-size: auto;\n",
-       "    }\n",
-       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
-       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
-       "    }\n",
-       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
-       "        background: #F44336;\n",
-       "    }\n",
-       "</style>\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
     {
      "data": {
       "text/plain": [
-       "{'Agkistrodon': 0.00013586886052507907,\n",
-       " 'Crotalus': 0.010002714581787586,\n",
-       " 'Lampropeltis': 0.00047056630137376487,\n",
-       " 'Masticophis': 0.0002429549494991079,\n",
-       " 'Micrurus': 0.00012576498556882143,\n",
-       " 'Natrix': 0.3323909044265747,\n",
-       " 'Nerodia': 0.6434937715530396,\n",
-       " 'Pantherophis': 0.0035959137603640556,\n",
-       " 'Tantilla': 0.00017943432612810284,\n",
-       " 'Thamnophis': 0.009362072683870792}"
+       "({'Agkistrodon contortrix': 7.677707714037751e-08,\n",
+       "  'Agkistrodon piscivorus': 6.286637017183239e-06,\n",
+       "  'Boa imperator': 4.072247179465194e-07,\n",
+       "  'Carphophis amoenus': 5.6490312090318184e-06,\n",
+       "  'Charina bottae': 5.74060948110855e-07,\n",
+       "  'Coluber constrictor': 2.58468026004266e-06,\n",
+       "  'Contia tenuis': 2.7349071842763806e-06,\n",
+       "  'Crotalus adamanteus': 2.228937091786065e-06,\n",
+       "  'Crotalus atrox': 3.808705969277071e-06,\n",
+       "  'Crotalus horridus': 1.1339221828166046e-06,\n",
+       "  'Crotalus pyrrhus': 1.3040776138950605e-06,\n",
+       "  'Crotalus ruber': 5.020022442181471e-08,\n",
+       "  'Crotalus scutulatus': 2.061498662442318e-06,\n",
+       "  'Crotalus viridis': 5.00088333410531e-07,\n",
+       "  'Diadophis punctatus': 7.539652528976148e-07,\n",
+       "  'Haldea striatula': 1.276449802389834e-05,\n",
+       "  'Heterodon platirhinos': 9.317946592091175e-07,\n",
+       "  'Hierophis viridiflavus': 9.718727369545377e-07,\n",
+       "  'Lampropeltis californiae': 5.61221838779602e-07,\n",
+       "  'Lampropeltis getula': 7.406313784485974e-07,\n",
+       "  'Lampropeltis triangulum': 1.079560024663806e-05,\n",
+       "  'Masticophis flagellum': 0.0001101287707570009,\n",
+       "  'Micrurus tener': 7.134622137527913e-07,\n",
+       "  'Natrix natrix': 3.180293560944847e-06,\n",
+       "  'Nerodia erythrogaster': 0.00011079021351179108,\n",
+       "  'Nerodia fasciata': 8.221828466048464e-05,\n",
+       "  'Nerodia rhombifer': 0.9991447925567627,\n",
+       "  'Nerodia sipedon': 5.9943962696706876e-05,\n",
+       "  'Opheodrys aestivus': 1.5374049326055683e-05,\n",
+       "  'Opheodrys vernalis': 6.054739856153901e-07,\n",
+       "  'Pantherophis alleghaniensis': 1.1153425475640688e-05,\n",
+       "  'Pantherophis emoryi': 1.006377146950399e-06,\n",
+       "  'Pantherophis guttatus': 1.3548749848268926e-05,\n",
+       "  'Pantherophis obsoletus': 4.6009528887225315e-05,\n",
+       "  'Pantherophis spiloides': 3.583466423151549e-06,\n",
+       "  'Pantherophis vulpinus': 3.0351711757248268e-05,\n",
+       "  'Pituophis catenifer': 1.9792829334619455e-05,\n",
+       "  'Regina septemvittata': 1.2407269423420075e-05,\n",
+       "  'Rhinocheilus lecontei': 2.616184065118432e-05,\n",
+       "  'Storeria dekayi': 2.0656678316299804e-05,\n",
+       "  'Storeria occipitomaculata': 1.0390400575488457e-06,\n",
+       "  'Thamnophis elegans': 1.6275485904770903e-05,\n",
+       "  'Thamnophis hammondii': 5.79929201194318e-06,\n",
+       "  'Thamnophis marcianus': 0.00016931473510339856,\n",
+       "  'Thamnophis ordinoides': 2.348029283893993e-06,\n",
+       "  'Thamnophis proximus': 1.092971160687739e-05,\n",
+       "  'Thamnophis radix': 2.1167873001104454e-06,\n",
+       "  'Thamnophis sirtalis': 1.695604260021355e-05,\n",
+       "  'Vipera berus': 3.6326639474282274e-06,\n",
+       "  'Zamenis longissimus': 2.3329607756750192e-06},\n",
+       " 'Belize, Guatemala, Mexico, Usa',\n",
+       " 'Nerodia rhombifer, commonly known as the diamondback water snake, is a species of nonvenomous natricine colubrid endemic to the central United States and northern Mexico. There are three recognized subspecies of N. rhombifer, including the nominotypical subspecies.',\n",
+       " 'Learn more: <a href=https://en.wikipedia.org/wiki/Nerodia_rhombifer>Nerodia rhombifer</a>')"
       ]
      },
-     "execution_count": null,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -478,26 +703,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "id": "21ab9dc4-c665-4847-b255-6e1135ebe716",
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/eleven/mambaforge/envs/fastai/lib/python3.10/site-packages/gradio/inputs.py:257: UserWarning: Usage of gradio.inputs is deprecated, and will not be supported in the future, please import your component from gradio.components\n",
-      "  warnings.warn(\n",
-      "/home/eleven/mambaforge/envs/fastai/lib/python3.10/site-packages/gradio/deprecation.py:40: UserWarning: `optional` parameter is deprecated, and it has no effect\n",
-      "  warnings.warn(value)\n",
-      "/home/eleven/mambaforge/envs/fastai/lib/python3.10/site-packages/gradio/outputs.py:197: UserWarning: Usage of gradio.outputs is deprecated, and will not be supported in the future, please import your components from gradio.components\n",
-      "  warnings.warn(\n",
-      "/home/eleven/mambaforge/envs/fastai/lib/python3.10/site-packages/gradio/deprecation.py:40: UserWarning: The 'type' parameter has been deprecated. Use the Number component instead.\n",
-      "  warnings.warn(value)\n",
-      "/home/eleven/mambaforge/envs/fastai/lib/python3.10/site-packages/gradio/deprecation.py:40: UserWarning: `enable_queue` is deprecated in `Interface()`, please use it within `launch()` instead.\n",
-      "  warnings.warn(value)\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -511,37 +720,39 @@
      "data": {
       "text/plain": []
      },
-     "execution_count": null,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "#| export\n",
-    "title = \"Snake Image Classification\"\n",
+    "title = \"Snake Species Identification\"\n",
     "\n",
     "description = \"\"\"\n",
-    "This demo is an ongoing iteration of a [bigger project](https://github.com/jimmiemunyi/the-snake-project) meant to classify snakes as venomous or non-venomous.\n",
+    "This demo is an ongoing iteration of the [Snake Species Identification](https://github.com/jimmiemunyi/the-snake-project-cls) project meant to classify snakes up to the species level (binomial name).\n",
     "\n",
-    "Currently, it can classify snakes into 10 genera.\n",
+    "Currently, it can classify snakes into 50 categories but it is continually updated to support more categories (over 200 for the final version).\n",
     "\n",
-    "The model can be found here: https://huggingface.co/Jimmie/snake-image-classification\n",
-    " \n",
+    "The model can be found here: https://huggingface.co/Jimmie/snake-species-identification.\n",
+    "The model is trained on the following dataset: https://www.aicrowd.com/challenges/snakeclef2021-snake-species-identification-challenge.\n",
     "\n",
     "Enjoy!\n",
     "\"\"\"\n",
     "\n",
-    "article = \"Blog posts on how the model is being trained: .\"\n",
+    "article = \"Blog posts on how the model is being trained: COMING SOON!\"\n",
     "\n",
     "\n",
-    "image = gr.inputs.Image(shape=(224, 224))\n",
-    "label = gr.outputs.Label()\n",
+    "image = gr.Image(shape=(224, 224))\n",
+    "label = gr.Label(num_top_classes=3, label='Binomial')\n",
+    "country = gr.Textbox(label='Countries where the species is found')\n",
+    "summary = gr.Textbox(label='Wikipedia Summary')\n",
+    "link = gr.HTML(label=\"Learn More:\", show_label=True)\n",
     "examples = list(path.ls())\n",
     "\n",
     "\n",
-    "intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples,\n",
-    "                   title = title, description = description, article = article,\n",
-    "                   enable_queue=True, cache_examples=False)\n",
+    "intf = gr.Interface(fn=classify_image, inputs=image, outputs=[label, country, summary, link], examples=examples,\n",
+    "                   title = title, description = description, article = article, cache_examples=False)\n",
     "intf.launch(inline=False)"
    ]
   },
@@ -555,7 +766,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "id": "eabe8427-b99a-415b-ba02-43c80822c118",
    "metadata": {},
    "outputs": [],
@@ -587,6 +798,18 @@
    "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.8"
   }
  },
  "nbformat": 4,