Fix example scripts in colab

example_model.ipynb

@@ -11,20 +11,20 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 1,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
         "id": "Ekw8Z93ljC3v",
-        "outputId": "675ac893-5a46-4c6b-dc03-09438941d1fc"
+        "outputId": "9787a091-e55b-483f-da7c-4c7ca80a7a33"
       },
       "outputs": [
         {
           "name": "stdout",
           "output_type": "stream",
           "text": [
-            "Python 3.10.12\n"
+            "Python 3.11.13\n"
           ]
         }
       ],
@@ -36,44 +36,38 @@
       "cell_type": "code",
       "execution_count": null,
       "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "yoy_wT1rhMqF",
-        "outputId": "4268fdb0-84d2-4502-97e4-e93a1440c8ee"
+        "id": "yoy_wT1rhMqF"
       },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m34.4/34.4 MB\u001b[0m \u001b[31m16.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-            "\u001b[?25h\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
-            "lida 0.0.10 requires fastapi, which is not installed.\n",
-            "lida 0.0.10 requires kaleido, which is not installed.\n",
-            "lida 0.0.10 requires python-multipart, which is not installed.\n",
-            "lida 0.0.10 requires uvicorn, which is not installed.\u001b[0m\u001b[31m\n",
-            "\u001b[0m"
-          ]
-        }
-      ],
+      "outputs": [],
       "source": [
         "# Install dependencies\n",
-        "!pip install -q numerapi pandas lightgbm cloudpickle==2.2.1 pyarrow scikit-learn scipy==1.10.1"
+        "!pip install -q --upgrade numerapi pandas lightgbm cloudpickle==2.2.1 pyarrow scikit-learn scipy==1.10.1"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 4,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 17
+          "height": 124
         },
         "id": "13hdRk9ghMqI",
-        "outputId": "857a4882-83e5-4a76-9b1e-57d6d822cc67"
+        "outputId": "85640501-eb59-46f6-bf67-bbc4ec7cff46"
       },
       "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "[LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.010098 seconds.\n",
+            "You can set `force_row_wise=true` to remove the overhead.\n",
+            "And if memory is not enough, you can set `force_col_wise=true`.\n",
+            "[LightGBM] [Info] Total Bins 210\n",
+            "[LightGBM] [Info] Number of data points in the train set: 688184, number of used features: 42\n",
+            "[LightGBM] [Info] Start training from score 0.500008\n"
+          ]
+        },
         {
           "data": {
             "application/javascript": "\n    async function download(id, filename, size) {\n      if (!google.colab.kernel.accessAllowed) {\n        return;\n      }\n      const div = document.createElement('div');\n      const label = document.createElement('label');\n      label.textContent = `Downloading \"${filename}\": `;\n      div.appendChild(label);\n      const progress = document.createElement('progress');\n      progress.max = size;\n      div.appendChild(progress);\n      document.body.appendChild(div);\n\n      const buffers = [];\n      let downloaded = 0;\n\n      const channel = await google.colab.kernel.comms.open(id);\n      // Send a message to notify the kernel that we're ready.\n      channel.send({})\n\n      for await (const message of channel.messages) {\n        // Send a message to notify the kernel that we're ready.\n        channel.send({})\n        if (message.buffers) {\n          for (const buffer of message.buffers) {\n            buffers.push(buffer);\n            downloaded += buffer.byteLength;\n            progress.value = downloaded;\n          }\n        }\n      }\n      const blob = new Blob(buffers, {type: 'application/binary'});\n      const a = document.createElement('a');\n      a.href = window.URL.createObjectURL(blob);\n      a.download = filename;\n      div.appendChild(a);\n      a.click();\n      div.remove();\n    }\n  ",
@@ -86,7 +80,7 @@
         },
         {
           "data": {
-            "application/javascript": "download(\"download_9cb9b662-7992-47b0-b787-453b845e7050\", \"predict_barebones.pkl\", 6572312)",
+            "application/javascript": "download(\"download_e0ab47e2-47f2-454e-849c-444ae3616723\", \"example_model.pkl\", 6482658)",
             "text/plain": [
               "<IPython.core.display.Javascript object>"
             ]